Total 419 Science / R&D / Research job vacancies in George Town

The A*STAR High Containment Biosafety Level 3 (BSL-3) Facility supports research and diagnostic work involving Risk Group 3 pathogens such as mpox virus, avian influenza, and Mycobacterium tuberculosis.

We are looking for a motivated Biosafety Officer to support biosafety operations and contribute to Singapore’s pandemic preparedness efforts.

Key Responsibilities

Biosafety & Compliance

• Support the development and implementation of biosafety policies, SOPs, and guidelines
• Conduct routine inspections and audits to ensure compliance with biosafety requirements
• Monitor adherence to approved biosafety practices and follow up on any gaps

Regulatory & Facility Coordination

• Liaise with internal stakeholders and regulatory authorities on biosafety matters
• Support facility certification activities, inspections, and emergency preparedness exercises
• Assist in coordinating safety-related meetings and addressing user queries

Biorisk Management & Stakeholder Support

• Provide support to Institutional Biosafety Committee (IBC) activities, including coordination and documentation
• Advise and support facility users on biosafety requirements and approval processes
• Contribute to institutional biorisk management efforts

Biological Materials & Documentation

• Coordinate the movement (import/export) and inventory tracking of biological materials
• Maintain accurate records of biosafety activities, training, and incidents

Training & Operations Support

• Assist in developing and delivering biosafety training programmes
• Provide day-to-day operational and administrative support to ensure safe and efficient facility use

Requirements

• Bachelor’s degree in Life Sciences, Microbiology, Biotechnology, or a related field
• At least 2 years of experience in BSL-2 or BSL-3 laboratory environments

• Must be a qualified Biosafety Coordinator/Officer recognised by MOH.

• Familiarity with biosafety principles and regulatory requirements

• Experience in audits, inspections, or SOP development is an advantage
• Strong organisational, communication, and documentation skills
• Comfortable working in a high-containment laboratory environment and using required PPE

• Familiarity with ISO standards (e.g., ISO 35001, ISO 9001) or GLP
• Experience in molecular biology, cell culture, or laboratory animal work

Applications should include full curriculum vitae and the names, addresses and contact numbers of 3 professional references.

We are seeking a proactive and detail-oriented scientist to support antibody engineering and functional evaluation within our next-generation biologics immune engager platform. This role focuses on experimental execution, assay development and molecular prototyping, contributing to programs with strong translational and partnership potential.

Position Impact

These positions form part of the Antibody Technology core, driving institutional innovation in next-generation antibody and immune-engager platforms that underpin future co-development partnerships and spin-off opportunities. Successful candidates will play a vital role in transforming scientific concepts into translatable therapeutic asset.

Key Responsibilities

• Conduct molecular cloning, protein expression, purification, and analytical characterization of antibody immune-engager candidates.
  
• Perform and optimize cell-based functional assays to assess potency, signaling, and immune activation.
  
• Support mono-specific and multi-specific prototype generation, screening, and data collection to evaluate molecular performance and mechanism of action.
  
• Maintain accurate experimental records, perform quantitative analysis, and contribute to internal data reviews and reports.
  
• Collaborate closely with scientists and engineers across discovery, design, and assay teams to ensure quality and timely delivery of milestones.
  
• Uphold high laboratory and data standards, contributing to a rigorous and collaborative team environment.

Experience & Qualifications

• B.Sc. M.Sc. And PhD in Biological Sciences, Biochemistry, Immunology, or related field, with (minimum of 8 years Bsc, Msc 5 years, PhD, 3 years of relevant hands-on experience.
• Practical skills in molecular biology, mammalian cell culture, and immunoassays (ELISA, FACS, reporter, cytotoxicity).
• Experience with protein expression systems (transient or stable) and purification workflows preferred.
• Strong analytical mindset, attention to detail, and ability to troubleshoot experiments independently.
• Team player with good communication, adaptability, and eagerness to learn new technologies in a fast-paced translational research setting.
• Experience with automation systems, liquid-handling platforms, or high-throughput screening.
• Working knowledge of data analysis software (e.g., GraphPad, FlowJo, Python/R) for experimental interpretation.
• Familiarity with protein characterization techniques (SEC-MALS, BLI, SPR, HPLC).
• Understanding of immune-cell biology or cytokine signaling mechanisms.
• Strong initiative, reliability, and enthusiasm to contribute to high-impact discovery programs.
• Prior experience in computational modelling is an advantage.
  

Job Description

The Signature Research Programme in Cardiovascular and Metabolic Disorders houses state-of-the-art technologies for profiling mitochondrial function and metabolic adaptations in human patients and other model organisms, and undertakes translational and clinical research in cardiovascular and metabolic disorders.

Dr Zhou Jin’s research focuses on molecular pharmacology to understand the mechanisms underlying disease, particularly dysregulation in mitochondrial function, autophagy, protein synthesis, and the activation of inflammation and fibrosis, with a strong emphasis on metabolic liver diseases. Her work integrates cell and molecular biology with preclinical disease models, alongside approaches such as transcriptomics, proteomics, metabolomics, and genetic analyses. Through these multidisciplinary strategies, her research aims to uncover novel molecular mechanisms of disease and support the development of new therapeutic strategies and potential treatment agents.

The selected candidate will perform a variety of functions related to research under the supervision of the Principal Investigator or his/her designate, including but not limited to the following: -

• Perform tasks and support all aspects of the research project.
• Conduct accurate monitoring, documenting and reporting of experimental results and/or research findings.
• Evaluate and interpret collected data and prepare oral presentations or written reports/ scientific manuscripts/literature for publication and analyses setting forth progress, adverse trends and appropriate recommendations or conclusions.
• Assist researchers in contributing to some aspects of the project management, occasional laboratory demonstrations and in providing guidance to undergraduate/medical students.
• Establish work procedures to maintain high efficiency and productivity of the laboratory.
• Assist with general upkeep of laboratory needs, maintain safety protocols, provide technical support and establish work procedures to ongoing research projects.
• Perform other related duties incidental to the work described herein.

Job Requirements

• Bachelor’s or Master’s degree in Sciences/Life Sciences with at least 2 years of relevant work experience in the design and conduct of experimental projects.
• Entry level candidates, with strong motivation to learn and achieve, may also be considered.
• Demonstrated good knowledge, skills and expertise in supporting various research activities including molecular biology, cellular assay.
• Knowledge of the scientific background relevant to the research area.
• Laboratory experimental skills.
• A strong team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.
• Experience with animal work (rodents) and RCULA certification is preferred but not required.

We regret that only shortlisted candidates will be notified.

About Us

At the Institute of High Performance Computing (IHPC), A*STAR, we drive innovation at the intersection of artificial intelligence and healthcare. Our mission is to build large language models (LLMs), agentic AI and multimodal foundation models that can transform clinical decision support, biomedical discovery, and public health. We are looking for AI Scientist strong applied AI skills ready to build large-scale systems, and you will contribute to innovations that make real impact in healthcare.

Key Responsibilities

Research & Development

• Develop novel architectures, training strategies, and optimization methods for LLMs, agentic AI, vision foundation model and multimodal foundation models.
• Advance instruction tuning, reinforcement learning (RLHF/GRPO), retrieval-augmented generation (RAG), and knowledge-grounded reasoning in medical AI.
• Design and implement multimodal learning pipelines that integrate text, imaging, omics, and real-world clinical data.

Translation & Collaboration

• Prototype AI systems for clinical and biomedical applications (e.g., decision support, conversational AI, population health, drug discovery).
• Benchmark models against state-of-the-art healthcare AI datasets and evaluation frameworks.
• Collaborate with industry and healthcare partners to enable translation, licensing, and commercialization.

Scientific Leadership

• Publish in top-tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL) and high-impact biomedical journals (e.g., Nature Medicine).
• Contribute to open science initiatives (datasets, model releases, benchmarks).
• Secure funding through collaborative research proposals with academia, healthcare institutions, and industry.

What We Offer

• Opportunity to push the frontiers of AI research while delivering real-world healthcare impact.
• A multidisciplinary environment with leading AI scientists, clinicians, and industry partners.
• Access to large-scale compute resources and unique biomedical datasets.
• Support for publications, conference participation, and translational pathways including licensing and spin-offs.

Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
• Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, ACL) or high-impact biomedical journals.
• Deep expertise in LLMs, vision foundation models, or multimodal AI.
• Strong skills in deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed/HPC training.
• Experience in large-scale LLM and/or foundation model training and deployment.
• Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics).
• Familiarity with biomedical ontologies and knowledge graphs (UMLS, SNOMED CT, PubMed).
• Understanding of AI ethics, safety, and regulatory considerations in healthcare.
• Opportunity to push the frontiers of AI research while delivering real-world healthcare impact.
• A multidisciplinary environment with leading AI scientists, clinicians, and industry partners.
• Access to large-scale compute resources and unique biomedical datasets.
• Support for publications, conference participation, and translational pathways including licensing and spin-offs.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Project Overview

In biopharmaceutical manufacturing, ensuring equipment is free from microbial contamination after cleaning is critical for product safety. Cleaning validation typically relies on compendial methods such as USP <61>, which assess microbial levels through culture-based techniques. However, these methods require multi-day incubation periods, specialized growth enrichment media, and manual operations, resulting in long turnaround times and increased risk of contamination during handling. The emergence of Rapid Microbial Methods (RMM) as state-of-art technologies seek to address these limitations posed by traditional compendial methods. Despite RMM having a shorter incubation period, the dependency of RMM on cells, high operator complexity and challenges in integrating process analytical technology (PAT) adds cost, time, and introduction of human error. This project aims to develop a novel, label-free microbial detection method, coupled with machine learning tailored for cleaning validation workflows.

This project is hosted within SMART-CAMP (Critical Analytics for Manufacturing Personalized-Medicine), an interdisciplinary research programme in Singapore (CREATE international research campus and innovation hub) and at the Massachusetts Institute of Technology (MIT). SMART CAMP addresses key technology bottlenecks in cell therapy manufacturing: (i) critical quality attributes of safe, effective cell therapy products; and (ii) integrated process analytics to monitor and modulate those attributes. This high-impact focus includes measurement and feedback control of processing parameters (process analytic technologies, or PAT) that contribute to cell viability and function during cell proliferation, and the measurement at intermediate and final steps of the cell product properties correlated with positive therapeutic outcomes (critical quality attributes, or CQA). This interdisciplinary team comprises engineers, biologists, clinicians, manufacturing, and data analytics experts from multiple MIT academic units, and multiple Singapore-based universities, research centres of excellence, and hospitals who are experienced at translational demonstrations of technologies in safety-regulated industries such as cell therapies.

Responsibilities

SMART-CAMP invites applications for a Postdoctoral Associate position in the area of microbiology and biotechnology, incorporating rapid detection tools and advancing them for testing in biopharmaceutical production. The successful candidate will be expected to work on the identification, verification, and design of ultraviolet spectroscopy and machine learning aided rapid and sensitive detection of micro-organisms, using a combination of microbiology, mass spectrometry and spectroscopic methods. This work will be conducted in close collaboration with a consortium of biopharmaceutical companies.

• This PDA will conduct feasibility studies of detection analytical methods based on metabolite detection of microorganisms to develop a rapid, sensitive diagnostic tool for safety screening.

• The PDA will take responsibility for testing and translating rapid methods for detection, as well as performing comparability/benchmarking experiments with compendial microbiology tests and molecular tests.

• Supervisory experience in junior researchers in all aspects of research.

The PDA will be expected to interface with technical staff from biopharma, as well as a research engineer to achieve the project objectives.

Requirements

• Ph.D. in microbiology, biotechnology, or relevant discipline.

• Demonstrable expertise in working with bacteria and/or fungi is desirable.

• An understanding of metabolite identification and quantification by LC-MS/MS, spectroscopic techniques is desirable. Experience or collaborative engagements involving machine learning / modelling is also viewed positively.

• Excellent verbal and written English communication skills are required.

• Strong interpersonal and relationship-building skills

• Self-motivated, independent, with superior collaborative, organizational and analytical skills

• Good track record of publication, IP and scientific output.

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

REPORTS TO: Middle & High School Principal

JOB GOAL: A High School Science teacher at ICS must have a strong understanding of the Next Generation Science Standards (NGSS) and have experience closing the achievement gap. They must develop engaging and innovative lessons that allow our students to grow academically, socially and emotionally. The teacher should be confident in incorporating technology (including emerging technologies such as GenAI) and hands-on learning experiences into the classroom with enthusiasm and also believe in collaboration with other colleagues, promoting understanding and communication in a diverse learning and cultural environment.

PERFORMANCE RESPONSIBILITIES:

• Plan, prepare, and execute appropriate lessons, utilizing appropriate resource materials and activities.
• Follow the prescribed scope and sequence of curriculum and assessment as scheduled.
• Employ a variety of instructional aides, methods, and materials that will promote best practices in order to reach the whole child as stated in the ICS mission statement.
• Assess student learning against the appropriate standards on a regular basis and provide progress reports as required.
• Identify the needs of students through diagnostic procedures and align instructional objectives to these needs.
• Effect student learning through mastery of the subject material by utilizing valid teaching techniques to achieve curriculum goals within the framework of the school’s philosophy.
• Eager to explore and learn about emerging technologies, such as Generative AI, with a commitment to integrating them effectively into the classroom to foster critical thinking and guide students in developing ethical and responsible use.
• Ensure Biblical Worldwide Integration (BWI) is mapped throughout the curriculum.
• Complete lesson/unit plans, Atlas, ESO documentation, and PLC expectations within specified time frames.
• Maintain student records as required by the school.
• Communicate with parents, students, and other professional staff regarding student progress (behavioral and academic).
• Follow school policies, procedures, rules, regulations, and guidelines and the provisions of the contract.
• Maintain proper discipline in the classroom and on the school premises utilizing teacher created discipline plans in conjunction with a school-wide discipline plan.
• Inform the administration if/when unable to fulfill any duty assigned. Prepare adequate information and materials for a substitute teacher.
• Plan and lead a student Chapel when called upon.
• Supervise extracurricular activities, organizations, and outings as assigned.
• Complete the Christian Philosophy of Education in-service program within the first three years of teaching at ICS.
• Attend and participate in devotions, teachers’ meetings, evening programs (if involving his or her students or as requested by the administration), and other meetings as assigned.
• Carry out supervisory duty as assigned (before school, break, lunch, after school).
• Maintain a classroom in a clean and educationally stimulating environment.
• Maintain regular and accurate attendance and grade reports that provide comprehensive information for each student’s learning progress.
• Keep students, parents, and the administration informed of students’ progress or deficiencies, and provide sufficient and timely notice to parents when students fail to meet learning standards.
• Submit all appropriate reports to the administration, guidance office, and business office as required by school regulations or as requested.
• Work with the administration in implementing all policies, procedures, and directives governing the operation of the school.
• Complete professional development programs as required by the administration and/or ICS Board.
• Maintain teaching credentials as required through sponsoring agencies (state/provincial education department, ACSI, etc.). Acquire and maintain teaching credentials as required by the laws of Singapore, NICS, and/or ICS.
• Demonstrate the character qualities of enthusiasm, courtesy, flexibility, integrity, kindness, self-control, perseverance, and punctuality.
• Exemplify strong interpersonal and communication skills.
• Meet everyday stress with emotional stability, objectivity, and optimism.
• Develop and maintain rapport with students, parents, and staff by treating others with friendliness, open-mindedness, dignity, and consideration.
• Respectfully submit to and demonstrate loyalty to constituted authority.
• Maintain a personal appearance that models cleanliness, modesty, good taste, and is in agreement with school policy.

QUALIFICATIONS:

• Bachelor’s Degree
• Teaching credential from a US state, Canadian province or from ACSI (exceptions will be approved by the Academic Board)
• Expertise in working with students and teaching Advanced Placement (AP) courses
• Knowledge of specific subject(s)

Job Description

The Cancer and Stem Cell Biology (CSCB) Programme studies the causes and treatments of cancer and related diseases. The CSCB research groups have diverse programmes in both basic cancer biology and clinical-translational studies, with a special emphasis on cancers that affect the Asian community in general.

The selected candidate will play an integral role in a natural products based drug discovery program, working both independently and collaboratively under the supervision of Prof Hendrik Luesch or his designate. The candidate will be responsible for analysing complex natural products using NMR and mass spectrometry, identifying potential molecular targets and mechanisms, conducting genome mining and heterologous expression studies, and carrying out a broad range of research activities. These activities include planning, organising, and executing research studies within the overall scope of the project under the supervision of the Principal Investigator or their designate, including but not limited to the following:

• Independently carry out the design and execution of experimental research required by the research component of the project.
• Write and review research papers, present research outcomes, conceptualise new ideas and develop plans for independent research which could have a considerable influence and impact on the relevant field attracting research funding.
• Provide support for external grant/protocol development, study design and management of research activities.
• Source financial support for research activities by investigating potential sources of funding, collaborate with Principal Investigator to write and revise grant/fellowship applications.
• Provide guidance and mentorship to research assistants.
• Maintain optimal experimental progress in the laboratory and assigned research work by conducting, supervising, and evaluating experimental procedures and outcomes, and by refining and analysing targets to ensure high-quality, reproducible results.
• Perform other related duties incidental to the work described therein.

Job Requirements

• PhD in Chemistry, Chemical Biology or related discipline.
• Demonstrated expertise in natural product isolation and characterisation.
• Strong proficiency in NMR and mass spectrometry for compound characterisation.
• Familiarity with dereplication databases and networking platforms (e.g., GNPS).
• Experience in metabolomics and global profiling.
• Ability to conduct independent literature searches.
• Proven track record of research publications and presentations.
• Strong writing and critical thinking skills, as well as good communication and presentation skills.
• A team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.

We regret that only shortlisted candidates will be notified.

About TUMCREATE

TUMCREATE is a multidisciplinary research platform of the Technical University of Munich (TUM) at the Singapore Campus for Research Excellence and Technological Enterprise (CREATE). We are partnering with universities, public agencies, and industry to advance future technologies.

Our public-private research partnership program, HEARTwise - Heart Failure Assessment with Reliable Technology using Wearables and In Vitro Diagnostics - is funded by Singapore’s National Research Foundation (NRF) and represents a collaborative effort between the Technical University of Munich (TUM), the National University Health System (NUHS), the National Heart Centre Singapore (NHCS), and the National University of Singapore (NUS).

As a member of the HEARTwise team, you will collaborate within an interdisciplinary consortium comprising leading experts in cardiology,telemedicine, biomedical engineering, acoustics, data privacy, and industry.

Please visit www.tum-create.edu.sg for more information about TUMCREATE.

Background & Scientific Context

Heart failure (HF) affects 2.5% of Singapore's population and is the leading cardiac cause of hospital admission -presenting a decade earlier and more aggressively than in Europe or North America. The 30% rehospitalization rate within 90 days of discharge is both a major clinical burden and a window of opportunity for early, data-driven intervention.

The HEARTwise project is a public-private research initiative funded by Singapore's National Research Foundation, bringing together clinical cardiologists (CADENCE / NUHS, NHCS),engineers from TUM and TUMCREATE, and MedTech partners. The project develops a multimodal platform for non-invasive, early decompensation detection in ambulant HF patients - combining wearable mobility sensing, acoustic environment recognition, and integration with additional digital biomarker sources.

This is a fixed-term contract until March 2029.

Supervision & Academic Environment

The position is jointly supervised by principal investigators at TUM Munich and TUMCREATE Singapore, with close integration into the CADENCE clinical network. The candidate will work within a growing team of researchers across engineering and clinical disciplines in Singapore, with strong links to the Munich ecosystem. The position combines the rigor of TUM's doctoral program with direct access to clinical partners and the unique research infrastructure of TUMCREATE.

The Research Position

This PhD is embedded in the HEARTwise engineering team at TUMCREATE Singapore and is centered on the actibelt®wearable technology platform - a body-worn 3D accelerometer system with a mature clinical track record, an established algorithm library, and over 64 years of recorded patient data. The core scientific contribution expected is the development, validation, and clinical deployment of actibelt-based mobility analysis in HF patients.

The candidate will engage with open methodological questions - including how to extract richer clinical information from inertial data, how to improve reference data acquisition for algorithm development, and what mobility-based signatures may carry predictive value for HF decompensation - as well as with the translational challenge of deploying these methods in a real clinical setting.

Central research questions include:

• Which mobility parameters derivable frombelt-worn inertial sensing are most informative for detecting early functionaldeterioration in ambulant HF patients?
• What methodological advances in reference data acquisition, sensor placement, or algorithm generalization can improve the quality and scalability of wearable-based gait analysis?
• How can a prototype clinical decision support tool effectively integrate actibelt-derived mobility markers with additional digital inputs to inform clinical management?

Your Responsibilities

Core project deliverables:

• Validate and adapt actibelt® technologyfor HF patient monitoring in Singapore, extracting and evaluating mobilityparameters (real-world walking speed, stair-climbing ability, gait qualityindices)
• Contribute to the design and executionof a clinical pilot study (35 HF patients + reference cohort) at NHCS/NUHCS
• Contribute to a prototype clinicaldecision support system integrating actibelt-derived parameters with additionaldigital inputs (e.g., digital stethoscope, digital scale)
• Publish findings in peer-reviewedjournals and present at international conferences
• Contribute to the CACOM lecture series(Clinical Applications of Computational Medicine, TUM)

Research and methodological development:

• Design and pursue original researchquestions within the project's scientific scope
• Develop and evaluate novel algorithmicapproaches for inertial signal processing, activity classification, or clinicalendpoint extraction
• Contribute to the broader actibeltalgorithm development pipeline, including work on reference data collectionmethodology and algorithm validation frameworks
• Engage across the HEARTwise consortium and bring your own scientific perspective to collaborative discussions

Required Qualifications:

• Master's degree (or equivalent) in Biomedical Engineering, Electrical Engineering, Computer Science, Data Science,Health Informatics, or a closely related field
• Strong interest in wearable technology,digital health, and translational research
• Solid programming skills (Python, R,MATLAB, Julia, or similar)
• Experience in signal processing,time-series analysis, or machine learning

Highly valued:

• Background in algorithm development forinertial, acoustic, or physiological sensor data
• Experience with clinical datasets orfamiliarity with clinical research environments
• Genuine curiosity about openmethodological questions and the ability to pursue them independently
• Ability to thrive in interdisciplinary teams spanning engineering, medicine, and data science
• Excellent communication skills in English

What we offer

• Fully funded PhD position within awell-resourced international collaboration
• Joint supervision by leading experts atTUM Munich and TUMCREATE Singapore
• Active engagement with a growinginterdisciplinary research team on-site in Singapore, with regular exchangeswith Munich
• Access to the TUM andCADENCE/CADENCE-Singapore networks (NUHS, NHCS, NTU, and beyond)
• Unique real-world clinical datasets anddeep access to the actibelt® technology platform and data ecosystem
• Genuine freedom to shape researchquestions within a meaningful applied and clinical context
• Support for conference participation,visits to Munich, and scientific publication

Applications

Please submit the following essential documents to hr@tum-create.edu.sg:

• CV
• Motivation letter (describing your research interests and why this position appeals to you)
• Academic transcripts
• Contact details of two referees

Only shortlisted candidates will be contacted.

We look forward to your application!

Job Description

We are looking for a highly motivated and skilled Research Assistant to join a project that integrates classical machine learning and AI with quantum computing on graphs datasets, with applications in drug development. The selected candidate will work on a research project of Duke-NUS AI + Medical Sciences Initiative (DAISI), which serves as the School’s hub for Academic AI and Data Science. This project will be conducted in collaboration with the Centre for Biomedical Data Science (CBDS) at Duke-NUS Medical School and the Centre for Quantum Technologies at National University of Singapore (NUS).

The selected candidate will perform a range of research activities focused on developing new AI algorithms and hybrid classic-quantum approaches for drug discovery under the supervision of the Principal Investigator or his/her designate. The candidate’s responsibilities will include, but are not limited to the following:

• Perform tasks and support all aspects of the research project.
• Carry out algorithmic development and data analysis.
• Implement state-of-the-art algorithmic improvements from recent literature in graph and geometric deep learning.
• Develop new geometric deep learning algorithms, from theory to experimental implementations, or adapting existing ones to problems in drug discovery.
• Perform other related duties incidental to the work described therein.

Job Requirements

• Bachelor’s / Master’s degree in a related scientific area (e.g., Physics, Mathematics, Computer Science) with demonstrated hands-on experience in developing deep learning, geometric deep learning, and generative AI algorithms. Candidates with higher credentials may be considered for Research Associate appointment.
• Experience with PyTorch, PyTorch Lightning, or equivalent deep learning frameworks.
• Proficiency in Python coding, with exposure to bash and multiprocessing environments.
• Familiarity with high-performance computing (HPC) environments and GPU programming.
• Strong teamwork skills with the ability to manage multiple priorities and thrive in a diverse work environment.

We regret that only shortlisted candidates will be notified.

What you’ll be doing:

• Conduct research on driving behavior related topics, such as future prediction, motion planning, agent simulation, scenario generation
• Work with large-scale internal datasets to demonstrate the effectiveness of your research
• Collaborate with different teams to deploy your research results into the autonomous vehicles 
• Publish the research results in papers and patents

What we are looking for:

• Enrolled in a Masters or PhD program in Computer Science, Electrical Engineering, Robotics or similar technical field of study
• Strong Machine Learning research background with publications in any of the top-tier conferences(RSS, ICRA, CoRL, CVPR, ICRL, ICML, NeurIPS, etc.)
• Proficiency in Python coding and PyTorch or other commonly-used deep learning frameworks
• One-team mindset and effective collaboration with other researchers and engineers
• Strong communication and interpersonal skills
• Previous experience in autonomous driving is preferred

Job Summary

Perform accounting and administrative tasks including accounts receivable and payable billing, data entry, and monthly reconciliation to support accurate financial records and smooth office operations.

Responsibilities

• Process accounts receivable (AR) and accounts payable (AP) to ensure accurate invoicing and payment tracking
• Perform monthly reconciliation of AR and AP to verify financial accuracy and resolve discrepancies
• Enter accounting data accurately to maintain up-to-date financial records
• Organize and file accounting documents to support record keeping and audit readiness
• Manage documentation related to daily accounting tasks to ensure compliance and accessibility
• Support administrative functions by ordering office supplies to maintain operational efficiency
• Assist with ad hoc assignments as needed to support team and organizational goals

Preferred competencies and qualifications

• Basic accounting knowledge demonstrated through relevant education (Minimum Nitec / O Level)
• Proficiency in Microsoft Office applications to perform data entry and documentation tasks
• Familiarity with MYOB or ABSS Accounting Systems to facilitate accounting processes
• Strong interpersonal and communication skills to collaborate effectively with colleagues
• Responsible work attitude and willingness to learn to adapt to evolving job requirements

Benefits:

• Five-day work week, Monday to Friday, 9am to 6pm
• Fourteen days annual leave
• AWS and Variable bonus
• Medical and insurance coverage

Interested candidate, kindly submit your application by clicking APPLY button.

The Signature Research Programme in Emerging Infectious Diseases (EID) aims to pioneer our understanding of emerging infections through world-class research that integrates immunology, infection biology, pathogen genomics, and computational approaches. This integration drives comprehensive studies of host–pathogen interactions across molecular, individual, and population scales to address emerging health challenges.

Antonio Bertoletti's Laboratory is focused on the development of new immunology-based therapies (TCR-redirected T cells and vaccine therapy) for the treatment of chronic HBV infection and hepatocellular carcinoma, and on the characterisation of adaptive virus-specific immunity in HBV, SARS-CoV-2, and emerging viruses (Nipah, Hendra, and SFTS virus).

We are looking for a talented Research Fellow to initiate and develop, under the supervision of the Principal Investigator, a project focused on the impact of ageing on human antiviral T cell immunity. Expertise in human immunology and antigen-specific T cell immunity will be highly valued.  The selected candidate will perform a variety of research activities, which include planning, organising and conducting research studies within the overall scope of research projects under the supervision of the Principal Investigator or his/her designate, including but not limited to the following: 

• Independently carry out the design and execution of experimental research required by the project.
• Write research papers, present research outcomes, conceptualise new ideas, and develop plans for independent research that could have considerable influence and impact on the field, including attracting research funding.
• Provide support for external grant and protocol development, study design, and management of research activities.
• Contribute to occasional educational and instructional activities and project management.
• Perform other related duties incidental to the work described therein.

Job Requirements

• PhD in Immunology or a related biomedical field in immunology and/or infectious diseases background.
• Have strong technical knowledge of immunological assays.
• Prior experience in the handling and management of BSL-2 clinical samples.
• Able to adapt to work with different clinical samples and research questions of interest.
• Demonstrated excellent quantitative, analytical, and organisational skills.
• Possess strong interpersonal and communication skills, with excellent written and oral English.
• A collaborative team player who is open-minded, self-motivated, and able to work effectively in an interdisciplinary team and diverse research environment.

We regret that only shortlisted candidates will be notified.

The Opportunity

The world of market research is changing fast, and so is Blackbox.

We are looking for a Research Manager (Insights Strategy and Innovation) to join our team at the intersection of human insights and technological evolution.

While you will be grounded in the fundamentals of high-quality research, this role is designed for a versatile professional who is energized by platform-based research models and the integration of AI and LLMs into the insights workflow. You will be responsible for ensuring the development of rigorous research, maintaining high-value client relationships, and driving quality delivery through both traditional and innovative execution.

A Week in the Life

This is a dynamic, hands-on role where you will span the entire research lifecycle. In any given week, you might find yourself:

• Co-designing complex discussion guides and questionnaires in a collaborative session with a client.
• Directly programming and testing interviews on our proprietary interactive platforms, such as Blackbox Dialogue.
• Analysing large datasets in Excel while utilising LLM tools to synthesize qualitative nuances at scale.
• Designing high-impact strategy decks in PowerPoint that translate data into clear business recommendations for your clients.
• Workshopping with our product developers to provide user feedback and optimise our next generation of research tools.
• Liaising with clients during kick-offs, reporting meetings, and in (many!) email exchanges.
• Contributing to sales and marketing efforts via proposal inputs, ideas for outbound outreach, and offering content for LinkedIn, Substack and our website.

Key Responsibilities

• Account & Project Management: Independently manage existing accounts, serving as a trusted point of contact to understand and deliver on client needs.
• Innovation & AI Integration: Actively use and advocate for AI/LLM tools to enhance personal productivity and contribute to the development of Blackbox’s proprietary solutions.
• Technical Rigor: Act as the bridge between strategy and operations. You will work closely with scripting teams (understanding logic in platforms like Forsta or Qualtrics), manage fieldwork vendors, and oversee the data processing phase (edit specs, table specs, and code frames).
• Analysis & Charting: Move beyond data entry to data storytelling. You will be responsible for charting, data visualization, and synthesizing information into reports that provide actionable value to clients.
• Strategic Reporting: Produce high-quality reports with actionable recommendations. You don't just report "what" happened; you explain "why" and "what’s next."
• Mentorship: Provide guidance and quality control for junior team members and interns, fostering a culture of precision and creativity.

Who You Are

We are looking for a candidate who is data-literate, tech-curious, and highly capable of multi-tasking across different workstreams.

• Experience: 4+ years of experience in market research, strategy consulting, policy analysis, or a related data-driven field.
  • We welcome applications from those outside the traditional market research industry (e.g., Management Consulting, Public Policy, or Business Intelligence) provided you possess strong analytical rigor and a passion for understanding human behavior.
• AI Proficiency: You are an "AI-native" professional, experienced in using LLMs and AI tools to streamline workflows and solve complex problems.
• Technical Familiarity: You should be comfortable with (or ready to master) research software (Forsta/Qualtrics), Excel for data management, and PowerPoint for storytelling. The ideal candidate will also have working knowledge of more advanced AI research tools.
• Communication: You have a proven track record in client management and the ability to synthesise complex information into clear, persuasive writing.
• Mindset: You are disciplined, self-motivated, and thrive in a fast-paced environment where you are expected to be both a thinker and a doer.

About the Job

We are looking for motivated candidates to join a vibrant and collaborative team of scientists and engineers in the Advanced Manufacturing & Semiconductor Division (AMS) at the Institute of High Performance Computing (IHPC), A*STAR. The successful candidate will contribute to research and development in physics-based modelling and scientific machine learning for semiconductor packaging reliability and multiphysics systems. This research explores new computational paradigms that integrate finite-element modelling, multiphysics simulations, and machine learning techniques to enable predictive modelling and accelerated analysis of complex physical systems relevant to advanced semiconductor packaging technologies. These include thermo-mechanical reliability of electronic packages, stress evolution in heterogeneous material systems, interfacial failure mechanisms, and process–structure–property relationships in packaging materials and architectures. You will work on R&D projects spanning fundamental methodology development and application-driven research, with opportunities to collaborate with interdisciplinary teams and industrial partners in the semiconductor ecosystem.

The key scope of work includes

• Integrating finite-element simulations and physics-based models with machine learning approaches for predictive reliability analysis.
• Developing data-driven surrogate models and reduced-order models for thermo-mechanical behaviour in electronic packaging structures.
• Developing high throughput computational workflows that combine multiphysics simulations, data analytics, and machine learning techniques.
• Contributing to the development of AI-enabled predictive frameworks for semiconductor packaging reliability and performance.
• Publishing research outcomes in leading journals and conferences in computational mechanics, semiconductor packaging reliability, and scientific machine learning.
• Collaborating with internal research teams, industry partners, and affiliated institutes on interdisciplinary R&D projects.

Job Requirements

• PhD degree in Mechanical Engineering, Computational Mechanics, Applied Mathematics, Computational Physics, or related disciplines.
• Strong background in numerical simulation and multiphysics modelling, particularly finite-element modelling of thermo-mechanical processes.
• Experience in modelling mechanical and thermal behaviour of materials and structures.
• Experience in data-driven modelling or machine learning approaches for physical systems.
• Strong programming skills in Python, MATLAB, or FORTRAN, with experience in scientific computing environments.
• Experience with simulation tools such as ABAQUS, ANSYS, COMSOL, or other multiphysics simulation platforms is advantageous.
• Experience with high-performance computing or large-scale simulations is an advantage.
• Strong analytical and problem-solving skills, with the ability to work both independently and collaboratively.

We particularly welcome early-career researchers who are passionate about advancing AI-driven modelling and predictive simulation technologies for semiconductor packaging reliability and multiphysics engineering systems.