Principal Scientist/Sr. Principal Scientist, Computational Chemistry & Molecular Design

Antares Therapeutics•Boston, MA

1d•$185,000 - $240,000•Hybrid

About The Position

We are seeking an exceptional computational chemist to serve as a scientific leader in molecular design across our discovery portfolio. As a member of a highly integrated team of medicinal chemists, machine learning scientists, structural biologists, biologists, and chemical biologists, you will apply and advance the full range of modern computational methods — structure- and ligand-based design, molecular dynamics, free energy perturbation (FEP), and machine-learning / generative approaches — to assess and prioritize targets, identify high-quality starting points, and drive lead optimization toward development candidates. This is a hands-on, high-impact individual-contributor role on the Antares scientific track. The successful candidate will not only enable programs directly but will also help shape the computational chemistry, machine learning and cheminformatics platform that underpins design across Antares. The role is offered at the Principal or Senior Principal Scientist level; scope, independence, and organizational influence scale with experience, as described under Qualifications.

Requirements

PhD. in computational chemistry, biophysics, theoretical chemistry, pharmaceutical sciences, cheminformatics, or a related quantitative field (or equivalent experience).
Principal Scientist: PhD with 10+ years (or bachelor's with 16+ years) of computational chemistry experience in a pharmaceutical and/or biotechnology setting. Senior Principal Scientist: PhD with 12+ years (or bachelor's with 18+ years), with a demonstrated track record of independent scientific leadership, cross-functional influence, and organizational impact.
Demonstrated, direct contributions to drug discovery programs through the application of computational chemistry — ideally including progression of compounds into or toward the clinic.
Deep, hands-on expertise across modern computational methods: structure- and ligand-based design, molecular dynamics, and free energy methods (e.g., FEP).
Proficiency with the Schrödinger suite and/or comparable platforms (e.g., MOE, OpenEye), and programming/scripting in Python and with coding assistants like Claude Code/Codex for cheminformatics and data analysis.
Strong understanding of medicinal chemistry, structural biology, and DMPK principles, and a proven ability to collaborate effectively in a fast-paced, matrixed, team-based environment.
Excellent written and verbal communication skills, with the ability to convey complex computational concepts to multidisciplinary audiences.
A passionate, results-oriented drug hunter who thrives in a collaborative, data-driven, and scientifically ambitious culture.

Nice To Haves

Experience applying machine-learning and/or generative molecular design methods in a discovery setting is strongly preferred.
Experience in covalent drug discovery — including covalent docking, warhead selection and reactivity/selectivity assessment, and modeling of covalent kinetics (e.g., kinact/Ki) — is strongly preferred and is central to Antares' programs.

Responsibilities

Serve as the computational chemistry function lead on programs, providing integrated leadership across target validation, hit identification, hit-to-lead, and lead optimization for multiple small-molecule programs.
Apply structure-based and ligand-based design, molecular dynamics, and free energy perturbation (FEP) to prioritize compounds, evaluate druggability, and identify and exploit cryptic or novel binding pockets on challenging targets.
Integrate machine-learning, generative, and active-learning approaches into design-make-test-analyze cycles, and multiparameter optimization of potency, selectivity, and ADMET/physicochemical properties.
Partner closely with medicinal chemistry to translate computational hypotheses into synthesized, tested molecules, and to drive sound decision-making and smart risk-taking.
Lead computational infrastructure and platform development — identifying, evaluating, and deploying best-in-class tools, methods, and workflows — and contribute to major collaborations with external partners, in coordination with the Discovery Predictive Sciences team.
Analyze and integrate data across functions to independently identify, define, and address critical scientific issues and key scientific questions.
Communicate analyses, models, and recommendations clearly to project teams and leadership, influencing program strategy and portfolio decisions.
Represent computational chemistry in cross-functional program teams; help set design strategy and define the questions that computation should answer at each stage.
Mentor junior scientists and, at the Senior Principal level, provide broad scientific direction, establish best practices, and act as a recognized technical authority internally and in the external scientific community.