Postdoctoral Associate Jobs in New York

Postdoctoral Associate

Required Qualifications: (as evidenced by an attached resume)

• A PhD (or foreign equivalent) in Computational Biophysics, Biochemistry, Chemistry, Bioinformatics, or a closely related quantitative field in hand by the start of the appointment.
• Demonstrated expertise in molecular dynamics simulation and enhanced-sampling techniques (e.g., Gaussian accelerated MD/GaMD, ligand GaMD).
• Experience building and interpreting Markov State Models or comparable approaches for identifying metastable states and conformational transitions.
• Proficiency in Python and standard molecular simulation/analysis tools (e.g., AMBER, VMD, PyMOL, Chimera, Cpptraj).
• A track record of first-author publications in peer-reviewed journals, and strong written and oral communication skills.

Preferred Qualifications:

• Experience in structure-based drug discovery workflows, including virtual screening, molecular docking (e.g., AutoDock Vina, Schrödinger), and free-energy/ADMET analysis.
• Prior work on kinase or other signaling-protein conformational dynamics, phosphorylation-driven activation, or allosteric regulation.
• Familiarity with machine learning and deep learning methods (e.g., variational autoencoders) applied to biomolecular dynamics data.
• Familiarity with elastic network modeling (ANM/GNM) or the ProDy software package.
• A track record of independent or co-led research projects and international conference presentations.

Brief Description of Duties:

The research group of Prof. Ivet Bahar, Director of the Laufer Center for Physical & Quantitative Biology at Stony Brook University, invites applications for a Postdoctoral Research Associate to join a program of work at the interface of structural dynamics, allostery, and computational drug discovery. The lab's guiding principle — “Bridging Structure & Function, via Dynamics” — investigates how the intrinsic flexibility and collective motions of biomolecules govern molecular recognition, allosteric communication, and functional adaptation across a wide range of disease-relevant systems.

The successful candidate will use enhanced-sampling molecular dynamics, coarse-grained elastic network models, Markov state modeling, and machine-learning methods to characterize the conformational dynamics and activation mechanisms of signaling proteins and other therapeutic targets, and to translate these mechanistic insights into structure-based and rational drug discovery. There is also scope to contribute to the group's ongoing work connecting structural dynamics to functional and disease-variant prediction (e.g., the Rhapsody framework) and to the group's broader efforts developing and disseminating open-source computational tools such as ProDy.

About the Group

The Bahar group develops and applies multiscale computational approaches — from coarse-grained elastic network models (ANM/GNM) to atomistic and enhanced-sampling molecular dynamics and machine learning/AI methods — to understand how biomolecules achieve diverse functions through flexible, dynamic structures. This work spans allosteric signaling, molecular recognition, and structure-function relationships, and supports the discovery of rational therapeutic strategies against cancer, neurological disorders, and drug-resistant infectious diseases. The group maintains an active, internationally collaborative research portfolio with experimental partners and is based at the Laufer Center for Physical & Quantitative Biology, a highly interdisciplinary research environment at Stony Brook University.

Duties:

• Investigate the conformational dynamics and allosteric activation mechanisms of signaling proteins and other disease-relevant targets (e.g., kinases, receptors, transporters) using classical and enhanced-sampling molecular dynamics (e.g., GaMD, LiGaMD) and coarse-grained elastic network models (ANM/GNM).
• Apply Markov State Models and machine-learning approaches (e.g., autoencoders, dimensionality reduction) to identify metastable conformational states and map activation and allosteric pathways.
• Conduct virtual screening, molecular docking, free-energy calculations, and ADMET profiling to support structure-based and rational design of small-molecule inhibitors and drug repurposing efforts.
• Contribute mechanistic, dynamics-based insight to one or more of the group's active research directions, including allostery, molecular recognition, and structure-based prediction of the functional impact of disease-associated variants.
• Collaborate with the group's network of experimental and computational partners to validate theoretical predictions.
• Co-author manuscripts for submission to leading structural biology, biophysics, and computational chemistry journals, and present research at group meetings, seminars, and international conferences.
• Contribute to the intellectual life of the Laufer Center (e.g., seminar series, mentoring of graduate/undergraduate students) as opportunities arise.
• Other duties as assigned.

Special Notes:
The Research Foundation of SUNY is a private educational corporation. Employment is subject to the Research Foundation policies and procedures, sponsor guidelines and the availability of funding. FLSA Exempt position, not eligible for the overtime provisions of the FLSA. Minimum salary threshold must be met to maintain FLSA exemption.

Applicants should submit:

• A curriculum vitae, including a full publication list.
• A cover letter (up to 2 pages) describing research background, interests, and fit with the group's research program.
• A brief research statement or summary of PhD/postdoctoral work (up to 2 pages).
• Contact details for two to three referees.

Visit The Office of Postdoctoral Affairs to learn more about our postdoctoral community.

Resume/CV and cover letter should be included with the online application.

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The starting salary range (or hiring range) to be offered for this position is noted below, it represents SBU’s good faith and reasonable estimate of the range of possible compensation at the time of posting.