Associate Director/Principal Computational Chemist
The candidate will establish GAIRI’s Chemogenomics program and develop statistical-learning approaches
The Genuity AI Research Institute (GAIRI) at HiberCell is seeking a highly motivated Computational Chemist to help pioneer the use of generative and supervised AI/ML in the biomedical sciences. The candidate will establish GAIRI’s Chemogenomics program and develop statistical-learning approaches to discover new molecules and chemical reactions for use in precision medicine and drug discovery, as well as to address disease etiology. They will provide internal expertise in computational chemistry methodologies, techniques, and tools. The ideal candidate must have deep understanding of the software tools, and the ability to use and adapt existing technologies.
Given the multi-disciplinary nature of the position, strong collaboration and communication skills are expected.
- M.Sc. in Chemistry, Computational Statistics, Computer Science, Computational Chemistry, Biostatistics, Cheminformatics, or related field with a minimum of 4-years of related industry and/or academic experience
- Experience in machine learning, deep learning, statistical methodology, predictive modeling and algorithm development to analyze large sets of chemical data.
- Familiarity with cheminformatic and bioinformatic tools and libraries such as RDKit and PubChem.
- Expertise in structure-based and/or ligand-based drug design (e.g., molecular docking, molecular dynamics, virtual screening, homology modeling, pharmacophore elucidation and QSAR).
- Familiarity with different types of 2D/3D molecular descriptors (e.g, fingerprints, SMILES, molecular graphs, etc.).
- Strong communication and presentation skills with the ability to translate and communicate results to individuals of diverse backgrounds
- Ph.D. and postdoctoral training in Chemistry, Computational Statistics, Computer Science, Computational Chemistry, Cheminformatics, or another related field with a minimum of 5 years of industry or academic experience
- Working knowledge of biology (oncology, immunology, autoimmunity, etc.) and experience in drug target identification
- Advanced programming skills with fluency in at least Python and/or R, with extensive experience using modern machine learning and deep learning libraries (eg., TensorFlow, sklearn, caret, etc.)
- Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS) with experience working with GPUs
- Experience with quantum computing algorithms
- Familiarity with quantum computing libraries such as Q#, PyQuil, Cirq, Qiskit, etc
- Up-to-date knowledge of the fast-moving AI/ML literature
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