Research Officer (Computational Chemistry & AI-Driven ADMET), BII

The Computational Therapeutics Innovation Group at Bioinformatics Institute (A*STAR) is seeking a highly motivated Research Officer to join our team. This position focuses on applying artificial intelligence (AI) and machine learning (ML) to accelerate early-stage drug discovery, particularly during the hit identification and hit-to-lead optimization phases.

The successful candidate will apply a combination of computational chemistry methods and AI/ML workflows for predicting target binding and ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) properties, to support early-stage drug discovery programs - guiding molecules from initial hits through to lead optimization. The role also involves interpreting prediction results to support compound prioritization and decision-making, with training and mentorship provided by experienced researchers.

Responsibilities

• AI/ML & Property Prediction: Develop, deploy, and maintain computational workflows and machine learning models for predicting compound ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties and target binding affinity.

• Data Curation & Cheminformatics: Clean, curate, and manage molecular datasets, chemical space exploration, and active learning loops to support computational workflows. Maintain accurate research records and ensure good data management practices.
• Support Drug Discovery Programs: Assist in the application of computational & AI/ML algorithms spanning multiple approaches (e.g., generative AI, active/reinforcement learning) to support multi-parameter optimization.
• Translational Collaboration: Collaborate with cross-functional teams to help select compounds and recommend ADMET assays for further testing, including planning in vitro assays and in vivo animal experiments alongside guidance from a senior staff member.
• Cross-Disciplinary Development: gain hands-on training in basic PK/PD modelling and simulation will be provided. Work with simple PK/PD projects in other workstreams may be required to get the necessary training in this aspect
• Communication & Documentation: Collect, analyse, and interpret research data, as well communicate findings through regular progress reports and presentations. Conduct literature reviews and contribute to scientific discussions within the team.

Requirements

• Bachelor’s or Master's degree in Chemistry, Cheminformatics, Pharmaceutical Sciences, Computer Science, Machine Learning, Bioinformatics, or a related discipline.
• Experience with computational chemistry software and its application to drug discovery.
• Experience with Python and scientific machine learning libraries (such as scikit-learn, RDKit, and chemprop).
• Strong analytical, organizational, and problem-solving skills.
• Ability to work both independently and collaboratively in a multidisciplinary research environment.
• Excellent written and verbal communication skills.
• Highly motivated, proactive, and eager to learn new computational methods.

Desirable

• Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow) and cloud or high-performance computing environments.
• Knowledge of medicinal chemistry, pharmacology, toxicology, and pharmacokinetics.
• Prior experience in biotech/pharma is advantageous.

Location: Computational Therapeutics Innovation Group, Bioinformatics Institute, A*STAR
Application enquiries: [email protected]

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.