Associate Computational Scientist- Pharmacological Sciences
Tasks
- Analyze transition paths and kinetic networks
- Build reproducible Python pipelines for GPU HPC
- Conduct structure based virtual screening and drug discovery
- Construct validate and interpret Markov state models
- Contribute to manuscripts grant applications and software documentation
- Develop adaptive sampling molecular dynamics workflows
- Develop and train large language models for biomedical tasks
- Model receptor ligand and protein interactions
- Perform enhanced sampling with metadynamics OPES and umbrella sampling
Perks/Benefits
- N/A
Skills/Tech-stack
Adaptive Sampling | Control Systems | Cryo-electron microscopy | Deep learning | Electron microscopy | Energy estimation | Enhanced sampling | Foundation Models | Free energy | Free energy estimation | GPU Computing | Generative deep learning | High Performance | High-Performance Computing | Kinetic modeling | Language Models | Large Language Models | Ligand docking | Linux | Machine Learning | Markov state modeling | Mean first passage time | Metadynamics | Molecular Docking | Molecular Dynamics | OPES | Performance Computing | Protein Ligand | Protein-ligand docking | Python | Quantitative Structure Activity Relationship | State Modeling | Structure-activity relationship | Transition path theory | Umbrella sampling | Version control | Version control systems | Virtual Screening
Education
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