Scientist (Computational Chemical Biology and Fragment-Based Design), BII
1 day ago
We are looking for a highly motivated computational scientist with a deep understanding of chemistry, cheminformatics, and structural biology to develop new AI models for ligand discovery. You will be working on a large collaborative project to build up A*STAR computational drug discovery capabilities. The candidate is expected to be familiar with the latest generative models. Familiarity with molecular dynamics simulations and docking software is a plus.
Key Responsibilities:
- Develop and implement AI-driven models for ligand discovery, with a focus on generative models.
- Collaborate closely with multidisciplinary teams to integrate computational methods with experimental research.
- Contribute to advancing A*STAR computational drug discovery capabilities, applying cutting-edge techniques in molecular modeling, machine learning, and data science.
- Stay abreast of the latest developments in AI and molecular modelling.
- Communicate research findings effectively, both in written and oral formats, to diverse audiences including scientific teams and stakeholders.
Job Requirements:
- Master or PhD degree in life sciences, chemistry, computational biology, biomedical engineering, or a related discipline.
- Passion for science and research.
- Highly motivated.
- Proficiency in the use of machine learning frameworks (e.g. PyTorch, TensorFlow).
- Experienced in developing generative models.
- Strong knowledge of chemistry, cheminformatics, and structural biology.
- Experience in performing molecular dynamics simulations and docking is advantageous.
- Able to work independently and as part of a team.
- Excellent written and oral communication skills.
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.
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