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

Job Summary 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 Essential - 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: james_lu@a-star.edu.sg

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