Research Assistant (CBDS/EP)

Job Description

We are looking for a highly motivated and skilled Research Assistant or Research Associate to join a project that integrates multi-omics analysis with machine learning and AI, with applications to target discovery. The selected candidate will work on one or more research projects of the Systems Genetics group led by Professor Petretto (Principal Investigator). This project(s) will be conducted in the Centre for Biomedical Data Science (CBDS) at Duke-NUS Medical School.

The selected candidate will perform a range of research activities focused on developing and applying computational biology, advanced bioinformatics and systems genetics for drug target discovery, as well as new ML/AI algorithms for discovery in complex diseases such as chronic kidney disease, idiopathic pulmonary fibrosis, or heart failure. Under the supervision of the Principal Investigator or his 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 data analysis and algorithmic development, including (but not limited to) single-cell and spatial transcriptomics.
• Implement state-of-the-art algorithmic improvements from recent literature in ML/AI integrative multi-omics analyses.
• Develop new deep learning algorithms, from theory to experimental implementations, or adapt/integrate existing ones to problems in drug target discovery.

Job Requirements

• ⁠Bachelor’s / Master’s Degree in a related scientific area (e.g., Bioinformatics, Computational Biology, ML/AI, Computer Science, Physics, Statistics, Mathematics, Biology, Medicine) with demonstrated hands-on experience in developing and/or applying algorithms for multi-omics data integration. Candidates with higher credentials may be considered for Research Associate appointment.
• Proficiency in R and/or 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.
• A solid understanding of genetics and genomics is desirable.

We regret that only shortlisted candidates will be notified.