Data Scientist (AIDD)

Job Description

The Singapore national program for the utilization of Artificial Intelligence (AI) in Drug Discovery (AIDD), funded by the Singapore National Research Foundation (NRF) and hosted by the Singapore Agency for Science, Technology and Research (A*STAR) seeks a talented and motivated AI Data Scientist to join our initiative. In this role, you will use multi-modal data and AI algorithms to bridge the gap between data and drug discovery advances, including agentic AI to orchestrate computational workflows. The primary emphasis of this role is small molecule drug discovery.  You will also interface with teams focused on the discovery and validation of novel biological targets.

Key Responsibilities

Cross-Modal Insight Generation

• Design and execute computational analyses that link data modalities from publicly available and proprietary sources to generate actionable hypotheses relevant to drug discovery.
• Contextualize experimental data and enable the translation of scientific findings by exploiting learned embedding spaces from AI models.  

Analytical and Agentic AI Workflow Development

• Develop reproducible analytical workflows for processing and analyzing multimodal datasets on the AIDD platform.
• Build data science tools and libraries to allow AIDD platform users to apply, interrogate and extend AI models in their own scientific workflows.
• Help to build and apply agentic AI workflows that leverage computational models and tools in the platform to enable the orchestration of multi-step scientific data analytics and reasoning tasks by chaining AI models, data queries and domain knowledge in automated pipelines with human oversight. 

Scientific Collaboration and Translation

• Collaborate with domain experts in AIDD to interpret, validate and contextualize AI models trained on relevant data modalities.
• Perform systematic evaluation and benchmarking of AI models and their latent representations.
• Develop and apply agentic AI workflows that can answer research problems encountered in drug discovery applications.
• Perform computational analyses and communicate the results to support drug discovery projects.

Qualifications

• PhD in fields such as: Computational Biology, Bioinformatics, Cheminformatics, Biomedical Informatics, Biomedical Engineering, Machine Learning, Artificial Intelligence or a closely related field.
• Strong domain expertise in small molecule drug discovery, and one or more of the following areas:Cheminformatics, structural biology, protein language modelsGenomics, transcriptomics, or other -omics data analysisPredictive and translational modeling
• Strong analytical and statistical skillsets.
• Strong experience using and training ML models.
• Proficiency in Python and scientific computing libraries (e.g., NumPy, scikit-learn, PyTorch).
• Familiarity with pre-trained foundation models and embedding-based analysis.
• Experience with agentic AI systems that incorporate reasoning and tool-calling.  

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.