The Research Fellow will participate in independent and collaborative research with a focus on DNA repair with an aim to advance translational research in breast cancer. You will be part of a dynamic, multidisciplinary environment comprising data scientists, laboratory researchers, and clinician scientists, which aim to advance translational research in breast cancer. You will also be responsible for overseeing wet-laboratory experiments, developing and optimizing data analysis workflows, mentoring junior researchers, and supporting research on patient derived models and mechanistic studies on breast cancer.
The responsibilities will include:
1) Research Contribution and Impact:
- Lead and supervise research projects relating to DNA repair, ecDNA, novel therapeutic targets and biomarkers in breast cancers.
- Carefully maintain and expand patient-derived breast model biobank.
- Evaluate and apply appropriate bioinformatics/statistical techniques, as well as develop and implement novel approaches to answer research questions.
- Prepare high quality visualizations, reports, and presentations for internal reviews, collaborations, and publications.
- Contribute to manuscript writing and presentation of research outcomes at internal and external conferences.
2) Mentorship and Supervision:
- Supervise Research Officers, PhD students and interns in conjunction with the PI.
- Communicate effectively with PI and team to troubleshoot protocols and workflow.
- Foster a collaborative and supportive work environment to contribute positively to team goals and outcomes.
3) Grantsmanship:
- Apply for independent grant funding.
- Assist with PI’s key research grant applications and reports throughout the year.
Requirements:
- Doctor of Philosophy (PhD) in Bioinformatics, Computational Biology, Genomics, Cancer Biology, or a related field.
- Demonstrated experience with basic and advanced lab techniques, including both cell and molecular biology techniques.
- Demonstrated experience with animal work.
- Familiarity with basic bioinformatics workflows.
- Good understanding of statistical methods used in biomedical research and profiling analysis.
- Excellent communication skills and ability to work in cross‑disciplinary teams.
- Proven ability to work independently and lead research initiatives.
- Experience developing or validating predictive models for clinical or translational research.
- Fluent in both written and spoken English.
