Total 5,338 Others level Education / Training job vacancies

Job Description

• Ensures proper investigational product (IP) management which includes sourcing, receipt, storage, preparation, dispensing, labelling, inventory accountability, reconciliation, retention, destruction and documentation according to the study protocol

• Assists Clinical Research Technologists in maintaining proper functioning of all pharmacy equipment.

• Reviews and provides feedback during protocol development where applicable

• Reviews and updates Pharmacy local standard operation procedures as appropriate

• Provides coaching to Locum Pharmacists and Pharmacy Technicians/Assistants as needed on IP management and aseptic compounding

Requirements

• Singapore Registered Pharmacist

• Previous Hospital Pharmacy Experience

• Experience in working in cleanroom or manufacturing setting

• General GMP and GDP knowledge

Interested candidates please send in your resume to:

clinicalresearch@recruitexpress.com.sg

EA Personnel: Valerie Yong Kian Fung

CEI No.: R1103704

Recruit Express Pte Ltd, EA License No.: 99C4599

Description:

• Lead applied research and strategic definition of machine learning algorithms, quantization methodologies, and toolchain capabilities for the Neural Network Development Kit (NDK) roadmap targeting next-generation Edge AI compute solutions
• Drive innovation at the intersection of ML algorithms and constrained hardware environments, identifying and validating the latest Edge AI technologies applicable to product requirements
• Serve as the primary technical interface between the AI Architecture team and the Software (Edge AI) team, delivering well-researched toolchain feature proposals and algorithmic specifications for implementation
• Collaborate with Software (Edge AI) and AI Architecture teams to identify and pursue targeted improvements in ML software methodology, and support Software-initiated improvement efforts with algorithmic insight and implementation guidance
• Maintain deep engagement with the global Edge AI research community to ensure the NDK roadmap reflects the state of the art in model efficiency, compression, and on-device learning

Key Responsibilities:

• Collaborate with the Sr. Design Manager (AI Architect) to define and maintain the NDK toolchain feature roadmap, ensuring alignment with the NPU hardware roadmap and overall AI product strategy
• Research, evaluate, and recommend quantization algorithms, pruning strategies, knowledge distillation techniques, and other model compression methodologies suited to constrained hardware targets
• Assemble and lead focused task forces drawing on partial bandwidth from the Software (Edge AI) and IC Design teams to prototype, benchmark, and validate proposed toolchain concepts before broader commitment
• Prototype and benchmark candidate ML algorithms and toolchain features to quantitatively demonstrate accuracy-performance trade-offs and justify roadmap prioritization

• Translate hardware architectural capabilities and constraints (as defined by the NPU Architect) into concrete toolchain feature requirements and algorithmic optimization opportunities
• Deliver comprehensive technical specifications and algorithmic documentation to the Software (Edge AI) team to enable confident and accurate implementation of NDK features
• Collaborate closely with the Software (Edge AI) team throughout the implementation phase to resolve algorithmic questions, validate correctness of implementations, and ensure performance targets are met
• Actively monitor and synthesize developments from the Edge AI research community — including publications, open-source frameworks, and industry benchmarks — to continuously inform and refresh the NDK roadmap
• Partner with the Software (Edge AI) team to jointly identify ML toolchain methodology improvement opportunities and drive those that originate from the AI Architecture team; provide expert advisory support for methodology improvements initiated by the Software team
• Evaluate and apply a range of productivity tools and techniques — including but not limited to AI-assisted methods — to accelerate algorithmic prototyping, benchmarking, and specification productivity
• Evaluate and integrate relevant open-source ML frameworks, runtimes, and toolchain components (e.g., MLIR, TVM, ONNX Runtime) as acceleration vectors for NDK development

Requirements:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or related technical field; PhD preferred, particularly in machine learning, optimization, or computer architecture
• 8+ years of experience in applied machine learning engineering or Edge AI software, with at least 5 years focused on model optimization, ML compilers, or on-device inference toolchain development
• Proven expertise in quantization (PTQ, QAT), pruning, knowledge distillation, and other model compression techniques with demonstrated results on resource-constrained hardware
• Strong knowledge of AI/ML algorithms, neural network architectures (CNNs, RNNs, Transformers, etc.), and the trade-offs between model accuracy, computational complexity, and memory footprint
• Demonstrated ability to stay at the forefront of the Edge AI research community, with a track record of translating academic and industry advances into practical product roadmap contributions
• Hands-on experience with mainstream ML frameworks (PyTorch, TensorFlow/Lite) and familiarity with ML compiler stacks such as MLIR, TVM, or ONNX Runtime
• Experience consuming hardware architectural specifications and translating them into software toolchain requirements and algorithmic optimizations
• Excellent communication skills with ability to present complex research findings and toolchain proposals clearly to architecture, software, and executive audiences
• Strong analytical and problem-solving abilities with emphasis on quantitative benchmarking, accuracy-efficiency trade-off analysis, and performance profiling on target hardware
• Demonstratedability to work collaboratively across team boundaries, including assembling and coordinating cross-functional task forces without direct authority
• Familiarity with RISC-V ISA and its software ecosystem, particularly in the context of AI inference deployment
• Experience with FPGA-based or simulator-based prototyping to validate algorithmic concepts against pre-silicon hardware models (preferred but not required)
• Self-motivated with ability to work independently, lead applied research initiatives, and drive toolchain innovation from algorithmic exploration through specification and successful team handoff

Job Description

The AI Research Scientist will contribute to clinical foundation model workstream for primary-care decision support. The role will focus on adapting open and/or institutionally approved foundation models to Singapore primary-care use cases, such as hypertension and cardiometabolic-renal multimorbidity scenarios involving diabetes, dyslipidaemia, CKD risk, medication burden, preventive care and follow-up planning.

The scientist will prepare structured training and evaluation data from clinical vignettes, synthetic cases, guideline-grounded Q&A, and eHINTS-like longitudinal data extracts where available. The role will support supervised fine-tuning, reinforcement learning or preference alignment experiments, and model evaluation against clinical templates, guideline compliance, safety constraints and usability requirements.

Key Responsibilities

• Prepare model-ready datasets from clinical vignettes, synthetic consultation cases, longitudinal records and guideline-derived tasks.
• Develop and run fine-tuning, instruction-tuning, preference-alignment and/or retrieval-augmented generation experiments for GP-oriented clinical tasks.
• Implement evaluation scripts for guideline adherence, factuality, safety alerts, medication recommendations, missing-data handling and structured output quality.
• Support multimodal and longitudinal data modelling where patient histories, lab trends, medications, notes and care plans need to be represented over time.
• Work with clinical collaborators to translate hypertension and multimorbidity requirements into model tasks, prompts, labels and acceptance criteria.
• Document experiments, datasets, model cards, limitations and reproducibility steps for internal review.

Required Qualifications and Skills

• PhD Degree in computer science, AI, biomedical informatics, computational science, data science or a related quantitative field.
• Hands-on experience with Python and modern deep-learning frameworks such as PyTorch, Hugging Face Transformers, vLLM or equivalent.
• Working knowledge of LLM fine-tuning, prompt engineering, retrieval-augmented generation, evaluation pipelines and reproducible ML experimentation.
• Ability to process structured and unstructured clinical data safely, including tabular records, notes, medications, lab values and guideline documents.
• Good understanding of model evaluation, error analysis, data quality control and responsible AI practices in healthcare or other high-stakes domains.

Preferred Experience

• Experience with clinical NLP, medical LLMs, healthcare datasets, FHIR/EMR-style data, or guideline-based decision support.
• Experience building synthetic data, simulation-based cases, or benchmark datasets for healthcare AI.
• Familiarity with primary-care chronic disease management, especially hypertension, diabetes, lipids, CKD risk and medication safety.
• Experience with GPU-based model training, experiment tracking, and deployment-oriented inference optimization. 

Job Summary

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 (Senior)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 & DevelopmentDevelop 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 & CollaborationPrototype 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 LeadershipPublish 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.

Qualifications

Minimum 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.

Preferred Qualifications

• 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.

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.

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking a highly motivated Senior Research Scientist to conduct cutting-edge research in Artificial Intelligence and Machine Learning, with a focus on advancing AI-driven scientific discovery across healthcare, life sciences, biology, and biomedical research.

The successful candidate will lead the development of next-generation AI technologies, including foundation models, multimodal learning systems, scientific machine learning, generative AI, and agentic AI systems that accelerate scientific discovery and translate research innovations into real-world impact.

Key Responsibilities

Research & Innovation

• Develop AI models and platforms that accelerate discovery in healthcare, life sciences, and biomedical research.
• Advance foundation models that learn from large-scale biological, clinical, molecular, and scientific datasets.
• Develop AI systems for:
• Multi-omics analysis
• Drug discovery and therapeutic development
• Precision medicine
• Biomarker discovery
• Disease prediction and prognosis
• Scientific knowledge extraction and reasoning
• Build agentic AI systems capable of hypothesis generation, experiment design, scientific reasoning, and autonomous discovery.
• Develop methodologies that integrate experimental data, simulations, scientific literature, and domain knowledge to support scientific decision-making and discovery.

• Collaborate with clinicians, biologists, healthcare researchers, and domain scientists to translate AI innovations into real-world applications.
• Drive the development of reusable AI platforms, foundation models, and scientific discovery systems.
• Contribute to technology transfer, intellectual property generation, and commercialization opportunities.
• Lead collaborations with academic institutions, healthcare organizations, government agencies, and industry partners.

Scientific Leadership

• Publish high-impact research in leading AI, machine learning, healthcare, and scientific journals and conferences.
• Contribute to grant proposals, project planning, and strategic research initiatives.
• Mentor junior researchers, engineers, and students.
• Represent IHPC in collaborations with academic, healthcare, government, and industry partners.

Requirements

Essential

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computational Biology, Biomedical Engineering, Computer Engineering, or a related discipline.
• Strong track record in AI/ML research demonstrated through publications, patents, or impactful projects.
• Strong programming skills in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
• Experience developing and evaluating machine learning and deep learning models.
• Experience working with large-scale datasets and computational infrastructure.
• Strong interest in applying AI to scientific discovery, healthcare, and life science challenges.

Preferred

• Experience in one or more of the following areas:Foundation Models for ScienceComputational Biology and Multi-OmicsDrug Discovery and Molecular ModelingBiomedical AIPrecision MedicineScientific Knowledge GraphsScientific Reasoning and Agentic AI SystemsHealthcare AI and Clinical Decision SupportGenerative AI for Scientific Discovery

What We Offer

• Opportunity to work on nationally significant AI for Science, Healthcare, and Life Sciences initiatives.
• Access to world-class computational infrastructure, large-scale scientific datasets, and advanced research facilities.
• Collaboration with leading AI researchers, clinicians, scientists, and industry partners.
• A dynamic environment supporting both fundamental AI research and translational impact.
• Opportunities to shape the future of AI-driven scientific discovery and healthcare innovation.

Job Summary

Role Overview

You will lead the institute’s efforts to identify emerging technology trends, market opportunities, and ecosystem shifts. In this role, you will oversee technology and market intelligence, assess the institute’s strengths against external opportunities, and shape clear recommendations on where to build, partner, or step back.

Key Responsibilities

• Oversee market and technology sensing to identify emerging trends, industry shifts, policy changes, and partnership opportunities.
• Lead technology intelligence — assessing emerging scientific areas, technical trajectories, maturity, standards, and competitive activity.
• Lead market intelligence — assessing industry needs, adoption barriers, value pools, investment trends, and partnership opportunities.
• Map the institute’s research strengths, platforms, talent, and partnerships against emerging opportunities.
• Develop clear recommendations on where to build, deepen, partner, or deprioritise capabilities.
• Build and lead a high-performance, engaged, multi-disciplinary team.

Requirements

• Advanced degree in science, engineering, or a related field. Postgraduate training is advantageous.
• Strong experience in market intelligence, technology intelligence, technology strategy, foresight, consulting, or innovation management.
• Ability to assess technology maturity, market opportunities, industry demand, competitive activity, and ecosystem developments.
• Strong analytical and communication skills, with the ability to turn intelligence into actionable strategic recommendations.
• High proficiency with Generative AI tools will be an advantage.

Career Growth & Impact

• Be the first to see what’s next. You will lead intelligence efforts across emerging technologies — from generative AI to quantum computing and green energy — with direct access to world-class researchers and labs.
• Build an unrivalled professional network. You will engage regularly with industry leaders, startups, government agencies, and international research partners.
• Turn insights into action. Your recommendations will directly determine where the organisation builds, partners, or steps back — a rare level of strategic influence for an intelligence role.
• Open doors across industries. This role is a springboard into technology strategy, corporate development, venture capital, or innovation policy.