Computational Chemist, PHD (30926)
Job Description
Job Description
Job ID: 30926
Contract Length: 1 Year (Renewable)
Title: Computational Chemist – Molecular Dynamics Simulation Expert
Duration: 12-Months Fixed-Term
Location: Waltham, minimum of 60% onsite
We are seeking an enthusiastic and talented Computational Chemist for a 12-month fixed-term position to contribute to the modeling of anti-tumor drug candidates.
About You:
You have a PhD (or equivalent experience) in computational chemistry, biophysics, structural biology, or a related field.
You have a proven track record with molecular dynamics simulation methodologies, including set-up, execution, and analysis
Preferably, you bring hands-on experience with coarse-grained MD approaches (such as MARTINI or related frameworks)
You are proficient in standard scientific programming/scripting (e.g., Python, Bash, or similar)
You communicate scientific concepts clearly, both verbally and in writing
Familiarity with other computational biophysics techniques (e.g., protein-protein docking, enhanced sampling)
Requirements: PhD
Years of experience: up to 10 years of experience is max
Phython and SAP skills are required.
Teams size: 6
Interview process: 1 virtual screen, then 1 panel interview, onsite if local.
You will drive molecular dynamics (MD) simulation to work on anti-tumor drug discovery projects. Your primary responsibility will be to develop, execute, and analyze MD simulations, with a strong emphasis on coarse-grained MD methodologies. You will collaborate closely with experimental scientists and other computational experts to provide structural and mechanistic insights that guide the design and optimization of drug candidates.
Key Responsibilities:
Design and conduct MD simulations to explore structure, dynamics, and interactions relevant to molecular interactions
Apply coarse-grained MD techniques and contribute to methodological improvements where possible
Analyze and interpret simulation results; effectively communicate findings to multidisciplinary project teams
Collaborate with experimental and therapeutic area colleagues to link modeling data to biological and pharmacological outcomes
Document methodologies, results, and best practices to enable knowledge transfer and reproducibility
TechData is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
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