IPST Postdoctoral Fellowship in Artificial Chemical Intelligence

The Institute for Physical Science & Technology (IPST), in close collaboration with the Institute for Health Computing (IHC) invites applications for postdoctoral fellowships in Artificial Chemical Intelligence — research at the interface of {Proteins ∪ RNA ∪ Chemistry} ∩ AI ∩ (Statistical Mechanics). 1 to 2 fellows will be hired to work with the Tiwary Lab and positions will stay open until filled. Applications will be considered on a rolling basis.

What you’ll do

You will develop and shape the future of AI for life and chemical/physical sciences. These will include methods that fuse AI with rigorous statistical mechanics (thermodynamics and dynamics) to tackle health- and energy-relevant problems where data is very limited. You will get direct and immediate feedback (in vitro, in cellulo etc.) from partners and collaborators across academic labs and industry partners. You will design models that embed physical constraints, learn ensembles from scarce/noisy measurements, and transfer across environmental conditions (e.g., temperature, solvent, concentration, cell type etc.), remaining robust, uncertainty-aware, and not brittle under distribution shift. You will collaborate with scientists in the Tiwary lab at IPST and the Institute for Health Computing as well as national lab and industry collaborators. There is a vast range of problems you can work on depending on your interests, including but not limited to:

• RNA/flexible proteins structural ensemble prediction and drug discovery

• predicting phase transitions in complex material systems

• extending timescales accessible to machine learned force fields

Qualifications

Publications demonstrating expertise in deploying and developing AI models, and domain expertise in at least one of proteins, RNA, or chemistry/molecular sciences generally; experience in statistical mechanics is desirable but not required. PhD in a science/engineering field by start; strong scientific computing and written/verbal communication skills. See this post for a flavor of what the interview process, if invited, might look like.

Support

$80,000 salary, full UMD benefits, $5,000 yearly research funds, and access to UMD’s Zaratan HPC. Initial 1-year term, renewable by one more year depending on conditions; flexible start; rolling applications.

What else will you gain

1. Career mentoring for academia and industry — job materials, interview/chalk-talk prep, and targeted networking.

2. Research independence and leadership — own projects, co-advise students and lead collaborations. 

3. Direct feedback on your computational predictions from a network of collaborators across different University of Maryland campuses, national labs and industry.

4. Tools, training, and visibility — access to different HPC and modern ML/simulation methods; national/international speaking opportunities and cross-academia/industry connections.

How to apply (email: ptiwary@umd.edu)

1. CV (≤2 pages) with publications + code repository link showing your work + contact info for 2 references.

2. Research statement (≤2 pages) outlining past work and future plans at the interface of {Proteins ∪ RNA ∪ Chemistry} ∩ AI ∩ (Statistical Mechanics), ideally based around one or two of the topics mentioned above. In your future plans please include a brief statement of how you see yourself helping society in 5, 10 and 20 years from now.