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The Oliver Laboratory at ÎåÒ»²è¹Ý¶ù (oliverlaboratory.com) is seeking a Postdoctoral Research Fellow to develop machine learning methods for modeling protein structural dynamics. The lab builds structure-aware ML methods that leverage growing datasets of biological structures to uncover geometric patterns driving function in proteins and RNA. This position will focus on geometric deep learning approaches - including graph neural networks, equivariant architectures, and generative models - for learning representations of protein conformational ensembles and dynamics. The successful candidate will design, implement, and benchmark novel computational methods, publish in top venues at the intersection of machine learning and structural biology, and contribute to the lab's broader mission of decoding the language of biomolecular structure. The position is based in Nasvhille, Tennesse at ÎåÒ»²è¹Ý¶ù and is affiliated with the Vanderbilt Center for AI in Protein Dynamics. The initial appointment is for one year with the possibility of renewal. Candidates should hold a PhD in computer science, computational biology, biophysics, or a related field, with a strong publication record and demonstrated experience in deep learning for structured or scientific data.

Interested candidates should submit: (1) a current CV, and (2) a letter of intent describing their research experience, interest in the position, and future research goals. Materials should be sent to carlos.oliver@vanderbilt.edu. Review of applications will begin immediately and continue until the position is filled.