1-3 Postdoctoral Fellows in Therapeutic Target and Drug Discovery Using Artificial Intelligence (AI) Coupled with Computational/Theoretical Chemistry

The Tiwary Lab at University of Maryland (UMD) go.umd.edu/tiwarylab aims to recruit between 1 to 3 Postdoctoral Fellows to work on projects for therapeutic target and drug discovery using Artificial Intelligence (AI) coupled with computational/theoretical chemistry. Projects are funded by various government and private sources.

*Salary and other details*

Fellows will receive a salary of $75,000/year, UMD benefits package, $5,000/year for professional development, and access to high-performance computing. The initial appointment is for 1 year, renewable for a maximum of another year.. Positions are available immediately and will remain open until excellent fits are found. The Fellowship will prepare you for competitive positions in academia or industry, with a focus on open-source software, publications and real world impact on critical problems in human health and therapy. No citizenship requirements.

*Scope of Work*

We aim to develop small molecule inhibitors and other therapies involving protein kinases, RNA and T cells. For this purpose, the selected Fellows will perform computational research at the intersection of statistical mechanics, molecular simulations, bioinformatics/cheminformatics and AI — collectively labeled as Artificial Chemical Intelligence — for tackling some of the most pressing scientific challenges facing society in therapeutics design, such as predicting drug residence times, anticipating drug resistance, identifying rare-yet-plausible receptor conformations and discovering cryptic binding sites. Many such difficult problems have inherently limited/poor quality data as well as intricate domain requirements dictated by complex physicochemical laws. For this the Fellows will develop/apply new paradigms that deeply and fundamentally integrate theoretical/computational chemistry with AI.  The AI-Chemistry integrated models include but are not limited to recent work from my group such as denoising diffusion probabilistic models pnas.org/doi/10.1073/pnas.2203656119, AlphaFold2-RAVE pubs.acs.org/doi/10.1021/acs.jctc.3c00290 and language models/recurrent neural networks in different flavors nature.com/articles/s41467-022-34780-x. See our full list of publications here: go.umd.edu/tiwarylab_publications  

You will be joining a collaborative, exciting, productive and diverse team of graduate students, postdocs and undergraduate researchers working on different projects (go.umd.edu/tiwarylab_group) The work will be carried out in close collaboration with and feedback from in vitro and in vivo experimental collaborators, including John Schneekloth at NCI for RNA, Markus Seeliger at Stony Brook for protein kinases and Grégoire Altan-Bonnet and Naomi Taylor at NCI for T Cells.

*Mandatory Requirements*

You should be close to defending PhD (in any subject) /have defended it in the last 1 year. You should have:

1. Expertise in using/developing ML/AI as demonstrated through first-author publications. Relevant research areas could include: generative models (e.g, diffusion models, VAEs), large language models, geometric deep learning, deep learning model assessment (evaluation, selection, interpretability).
2. Expertise in any one or more of the following, as demonstrated through first-author publications: large-scale biomolecular simulations;  protein/RNA structure prediction and protein/drug design using any approach; bioinformatics/cheminformatics.

*How to apply*

The Tiwary Lab values and promotes inclusivity, and warmly welcomes applicants from all diverse backgrounds to apply. Please email your application to ptiwary@umd.edu, including a CV and cover letter. After passing an initial screening, qualified candidates will be provided with programming exercises to assess their skills.

We are also looking for graduate students to work with us starting fall 2024. You can apply to us through chemistry PhD program or any of the 3 biophys/chemphys/applied math & scientific computing programs at IPST. We welcome students from diverse undergraduate majors including but not limited to chemistry, biophysics, physics, materials science and applied math.