Posted: Feb. 01, 2021
Silicon Therapeutics (“SITX”) is a privately held, physics-driven integrated drug discovery company. SITX’s discovery efforts as well as physics-based platform are all completely in-house, with a full wet lab as well as a team of experienced R&D professionals spanning biology, biochemistry, chemistry, biophysics (NMR + X-ray) & preclinical sciences. SITX’s engine leverages quantum mechanics and molecular dynamics, which are deployed on its own internal supercomputer composed of over 400 GPU’s and FPGA’s and allows SITX to accurately simulate the physical motion and properties of biological targets at an atomistic level resolution. We are the only company that owns the entire spectrum of physics-driven drug discovery from chip-to-clinic with a team of approximately 70 individuals in Boston.
Our diversity and our cross-functional, multi-dimensional teams make us strong. We foster an open-minded culture where we come to work without preconceptions about how people think. With all channels open for communication, we can rapidly fuse information across disciplines and teams.
Silicon Therapeutics is looking for a highly motivated Research Scientist with experience in molecular dynamics (MD) simulations of protein complexes and applications of machine learning (ML) for simulation analysis. She/he will be responsible for exploring conformational dynamics of protein-protein complexes to predict binding and signaling. This position will involve methodological developments to push the boundaries of what is possible using a large distributed computational infrastructure of GPUs and CPUs. Python programming and simulation analysis experience is required, with an emphasis on advanced simulation techniques such as Umbrella Sampling, Markov State Modeling, or Weighted Ensemble. Experience with machine learning of proteins and small molecules is a plus.
• Design, run, and analyze advanced simulations to explore the conformational dynamics of protein-ligand and protein-protein interactions.
• Perform and analyze simulations at scale (hundreds to thousands of simulations).
• Work closely with experimental scientists to incorporate structural and dynamical data into simulations, and to use data for simulation validation.
• Work closely with Silicon Tx scientists in our drug discovery efforts.
• Investigate latest simulation and experimental trends and propose adoption where appropriate.
• Work closely with Silicon Tx research programmers to implement and test new methods.
• Ph.D. in Computational Chemistry, Computational Biology, Biophysics, Computer Science, or a related discipline, with a specific focus on applications of molecular dynamics simulations.
• Extensive knowledge of, and experience with, molecular dynamics simulations of protein-ligand or protein-protein systems.
• Demonstrated ability to program in Python.
• Strong interpersonal, communication, and teamwork skills.
• Ability to conduct independent research.
Additional Preferred Qualifications
• Experience applying machine learning to structural questions for proteins and ligands.
• Experience with advanced simulation methods for path sampling, such as milestoning, Weighted Ensemble, metadynamics, and Markov State Models.
• Experience with free energy and binding kinetics calculations.
• Desire for leadership and to mentor other investigators.
• Industrial experience using simulations in a drug discovery setting.
• Strong publication record.
Silicon Therapeutics provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.Apply