Scientist/Senior Scientist, EDDC

Experimental Drug Development Centre (EDDC) is a drug discovery national platform in Singapore focused on translating upstream research into therapeutic assets to generate value for Singapore. EDDC is looking for a scientist/senior scientist to join the Computational Chemistry team to strengthen our efforts in computer-aided and AI approaches for small molecule drug discovery.

As part of the team, the candidate will be developing and applying cutting-edge computational methods such as Molecular Dynamics simulations and Free Energy Perturbations to study molecular mechanisms underpinning protein-ligand and protein-protein interactions and their binding affinity/kinetics for small molecule drug discovery projects. The staff will also have the opportunity to collaborate closely across functions, with biologists and chemists to support hit identification, hit-to-lead design, and lead optimization, as well as with AI scientists to develop machine learning models for in-house discovery programs.

Key Requirements

• Minimal 2 years of working experience in a similar role or 3-5 years of working experience (in academia) after PhD study
• Good knowledge in chemistry and protein structure with basic knowledge in medicinal chemistry
• Experience in applying molecular simulation software (e.g. Amber, Gromacs, Desmond, NAMD)
• Track record of scientific publications in the field (>5 first-authored publications in reputable computational chemistry/biology journals)
• Personal attributes of independence, integrity, creativity, problem-solving, team player, excellent communication skills, and strong work ethic

Candidates with the following will have better standing:

• Expertise in structure-based drug design, molecular dynamic simulations including enhanced sampling (REMD, GaMD, Metadynamics, Markov State Model, etc.) and free energy perturbations (ABFE, RBFE); quantum chemical simulations
• Fluent in at least one scripting or programming language (e.g. Python)
• Working knowledge of applying machine/deep learning approaches to solve relevant biological or chemical problems is a plus

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria.