Scientist, AI/ML for Drug Discovery

Job Description

We are seeking a highly motivated and skilled Biomedical Researcher to join our dynamic team. The successful candidate will contribute to cutting-edge research focused on therapeutics discovery and development. This role will involve designing and conducting experiments, analyzing complex datasets (including biological and clinical data), integrating and developing Artificial Intelligence (AI) models for data analysis and prediction, and disseminating research findings through publications and presentations. The ideal candidate will possess a strong foundation in biomedical sciences, proficiency in programming, and a growing expertise in the application of AI/Machine Learning to biomedical challenges.

About our Lab:

Our team is focused on structure and function of RNA and applications of RNA for therapeutics and as a drug target. We are a computational team using physics-based and statistical AI/ML models to identify functional elements in RNA and discover ways to target these regions for therapeutic purposes, particularly in infectious disease and cancer. 

Responsibilities:

• Research Design & Execution: Design, conduct, and analyze experiments for therapeutics development. This includes experimental planning, data collection, quality control, and troubleshooting.
• Data Analysis: Analyze complex biological and clinical datasets utilizing statistical methods and programming languages.
• AI/ML Model Integration & Development: Integrate existing AI/ML models into research workflows and contribute to the design, training, and validation of novel models for tasks such as affinity prediction for de-novo drug design.
• Programming & Scripting: Develop and maintain scripts and tools for data processing, analysis, and visualization using languages such as Python, C++, or similar.
• Literature Review & Scientific Writing: Stay current with relevant scientific literature, critically evaluate findings, and prepare manuscripts for publication in peer-reviewed journals.
• Collaboration & Communication: Collaborate effectively with other researchers, present findings at conferences and meetings, and participate in team discussions.
• Grant Support: Contribute to the preparation of grant proposals and reports.

Qualifications:

• Education: PhD in Biomedical Science, Bioinformatics, Computational Biology, or a closely related field.
• Research Experience: Demonstrated research experience in drug discovery with a strong track record of scientific productivity (e.g., publications, presentations).
• Programming Skills: Proficiency in at least one programming language (e.g., Python, R, MATLAB) with experience in data manipulation, statistical analysis, and visualization.
• AI/ML Familiarity: Familiarity with AI/ML concepts and techniques, including supervised and unsupervised learning, deep learning, and model evaluation. Experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is highly desirable.
• Model Design/Training Experience: Experience in designing, training, and validating AI/ML models, preferably in a biomedical context.
• Communication Skills: Excellent written and oral communication skills, with the ability to effectively communicate complex scientific concepts to both technical and non-technical audiences.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to critically evaluate data and draw meaningful conclusions.
• Collaboration: Ability to work effectively both independently and as part of a team.
• Attention to Detail: Meticulous attention to detail and a commitment to scientific rigor.

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.