AI in Computer-Aided Drug Design
ABG-125419 | Thesis topic | |
2024-08-07 | Public funding alone (i.e. government, region, European, international organization research grant) |
- Chemistry
- Computer science
- Physics
Topic description
You will develop and apply novel techniques for Computer-Aided Drug Design. The major focus will be on artificial intelligence (AI), virtual screening, data-driven structure-based design, and free energy simulations. Of particular interest are predictive and generative graph neural networks (GNN). You will provide a major contribution to translational projects in collaboration with medicinal chemists and biologists in academia and the industry. Therapeutic areas include cancer, aging and neurologic disorders and involve innovative biomolecular targets.
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Kireev lab develops and applies computational tools to advance our understanding of complex biological systems and discover therapies for unmet medical needs. Specific research activities include (i) translational projects in collaboration with the biologists and medicinal chemists, (ii) developing novel techniques for computer-aided drug design, and (iii) multiscale-simulations of large biological systems. After winning Critical Assessment of Hit-finding Experiments (CACHE) Challenges twice in a row, Kireev lab emerged as an international leader in virtual screening.
https://chemistry.missouri.edu/people/kireev
https://chemistry.missouri.edu
The University of Missouri (Mizzou or MU) is a public land-grant research university in Columbia, Missouri. It is Missouri's largest university that was founded in 1839 and was the first public university west of the Mississippi River. It has been a member of the Association of American Universities since 1908 and is classified among "R1: Doctoral Universities – Very high research activity". Enrolling 31,401 students in 2021, it offers more than 300 degree programs in thirteen major academic divisions. The University of Missouri Research Reactor Center is the United States’ sole source of isotopes used in nuclear medicine. Two alumni and faculty have been awarded the Nobel Prize.
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Candidate's profile
You are expected to have a solid background in one or more of the following: Chemoinformatics, machine learning, virtual screening, physical chemistry, molecular dynamics, programming languages. You are also expected to have a broad interest in biomedical sciences. You must display outstanding motivation and commitment to research in a fast-moving and competitive field. Excellent personal skills and the ability to work in a multidisciplinary team setting are essential.
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