Associate Computational Scientist- Pharmacological Sciences
About The Position
The Associate Computational Scientist will assist laboratory personnel in computational studies aimed at elucidating the kinetic and thermodynamic mechanisms by which ligands with varying efficacies, including positive allosteric modulators (PAMs) regulate the activation and signaling of G protein-coupled receptors (GPCRs), with particular emphasis on the μ-opioid receptor. The research combines long-timescale molecular dynamics simulations, adaptive sampling, enhanced sampling techniques, and Markov state modeling (MSMs) to characterize transient conformational states and quantify ligand-dependent transition pathways that are inaccessible to experimental structural biology alone. The project integrates computational structural biology with cryo-electron microscopy to determine how allosteric modulators alter receptor activation kinetics, signaling efficacy, and receptor-transducer interactions. These mechanistic insights will guide the rational discovery and optimization of novel PAMs that enhance therapeutic efficacy while minimizing adverse effects, thereby accelerating the development of safer analgesics and other GPCR-targeted therapeutics. The position will also contribute to (a) the development of generative deep learning frameworks for GPCR dynamics that infer collective variables and conformational landscapes from molecular simulations, enabling efficient sampling of receptor activation pathways and predictive modeling of signaling kinetics, and (b) the training and application of large language models using real-world data.
Requirements
- Computational studies experience.
- Experience with long-timescale molecular dynamics simulations.
- Experience with adaptive sampling techniques.
- Experience with enhanced sampling techniques.
- Experience with Markov state modeling (MSMs).
- Experience integrating computational structural biology with cryo-electron microscopy.
- Experience developing generative deep learning frameworks.
- Experience inferring collective variables and conformational landscapes from molecular simulations.
- Experience with predictive modeling of signaling kinetics.
- Experience training and applying large language models.
Responsibilities
- Assist laboratory personnel in computational studies.
- Elucidate kinetic and thermodynamic mechanisms of ligand regulation of GPCR activation and signaling.
- Utilize long-timescale molecular dynamics simulations, adaptive sampling, enhanced sampling techniques, and Markov state modeling (MSMs).
- Characterize transient conformational states and quantify ligand-dependent transition pathways.
- Integrate computational structural biology with cryo-electron microscopy.
- Determine how allosteric modulators alter receptor activation kinetics, signaling efficacy, and receptor-transducer interactions.
- Guide the rational discovery and optimization of novel PAMs.
- Contribute to the development of generative deep learning frameworks for GPCR dynamics.
- Infer collective variables and conformational landscapes from molecular simulations.
- Enable efficient sampling of receptor activation pathways and predictive modeling of signaling kinetics.
- Train and apply large language models using real-world data.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
