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Molecular Docking Jobs (NOW HIRING)

OpenEye Scientific

$101K - $188K/yr

Knowledge of some traditional computational chemistry approaches such as docking, virtual screening, molecular modeling, etc. * Programming expertise, ideally in c++ and/or python preferably with ...

Chemify Ltd

Staff CADD Scientist

San Francisco, CA · On-site +1

We are creating a future where the synthesis of previously unimaginable molecules, drugs, and ... Deploy and advance methods across the CADD stack - docking, pharmacophore, shape and 3D-similarity ...

University of Colorado

Temporary Researcher

Boulder, CO · On-site

$25/hr

Job Summary The Molecular, Cellular, and Developmental Biology department at CU Boulder invites ... Familiarity with computational tools for peptide design and docking (e.g., AlphaFold, ProteinMPNN)

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Molecular Docking information

What is a Molecular Docking job?

A molecular docking job involves using computational techniques to predict the interaction between molecules, such as a drug candidate and a target protein. Researchers in this field use specialized software to model binding affinities, optimize molecular structures, and analyze potential therapeutic effects. This role is often found in pharmaceutical research, bioinformatics, and drug discovery, requiring expertise in molecular modeling, chemistry, and computational biology.

What are the key skills and qualifications needed to thrive in the Molecular Docking position, and why are they important?

To thrive in a Molecular Docking role, you need strong expertise in computational chemistry, structural biology, and molecular modeling, often supported by an advanced degree in a related field. Familiarity with molecular docking software (such as AutoDock or Schrödinger Suite), programming languages (like Python or R), and experience with high-performance computing are typically required. Attention to detail, analytical thinking, and effective communication are valuable soft skills for collaborating and presenting complex findings. These capabilities are essential for accurately predicting molecular interactions, driving scientific discovery, and contributing to successful multidisciplinary projects.

What does a typical day look like for someone working in Molecular Docking?

A typical day in Molecular Docking often involves running computational simulations to predict how small molecules interact with biological targets, analyzing and interpreting the resulting data, and preparing reports or presentations for research teams. You may also spend time troubleshooting software issues, developing scripts to automate workflows, and staying up to date with the latest scientific literature. Collaboration is common, as you’ll likely work closely with medicinal chemists, structural biologists, and other computational scientists to refine hypotheses and guide experimental design. This multifaceted environment provides opportunities to continually learn and apply new techniques, making the day-to-day work both intellectually stimulating and impactful.

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Molecular Docking jobs near you

Senior Data Scientist, Computational Chemistry

Parabilis Medicines

Cambridge, MA • On-site

Full-time

Posted 4 days ago

Job description

About Parabilis Medicines
Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines for patients with serious diseases by unlocking biologically important targets long considered undruggable. The company has pioneered a new class of alpha-helical peptides - Helicons™ - capable of modulating intracellular proteins that have historically been beyond the reach of conventional medicines. The company's lead investigational medicine, zolucatetide, is the first and only direct inhibitor of the β-catenin:TCF interaction, a central node in the Wnt/β-catenin pathway that has eluded drug developers for decades. Zolucatetide is being evaluated in the clinic across multiple Wnt/β-catenin-driven diseases, including desmoid tumors, familial adenomatous polyposis (FAP) and a range of other solid tumor indications. Beyond zolucatetide, Parabilis is advancing additional Helicon-based programs focused on other challenging targets where we believe our medicines could have life-altering impact. For more information, visit www.parabilismed.com or follow us on LinkedIn.
What's the opportunity?
We are seeking a highly talented and self-motivated person to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Parabilis's platform discovery engine for HeliconTM stapled-peptide drugs. The skill sets of the group includes state-of-the-art machine learning/generative AI, molecular modeling, cheminformatics and data science towards the discovery and development of HeliconTM stapled-peptide drugs.
You'll be part of a data science team that is a central pillar of Parabilis's innovative discovery platform and pipelines targeting "undruggable" genes of major therapeutic interest to patients. Our data science team is an integrated team, ranging from computational biology, bioinformatics, computational drug discovery, research informatics and engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science, from building the discovery pipeline to supporting and developing our discovery .
Responsibilities
  • Provide computational expertise towards, but not limited to, ternary complex designs for degraders and other proximity-based modalities, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments and advancing drug-pipeline projects towards the clinic.
  • Identify, implement, and apply 3D modeling techniques for sampling HeliconTM peptide conformations in presence of a target, in ternary complex, and in different physiological environments.
  • Analyze and derive 3D peptide-structure relationships.
  • Exemplify scientific leadership by partnering across functions and working within a team of talented and passionate scientists to discover drugs.
  • Interface with internal and external partners.

What you'll need to be successful:
  • PhD in Computational Chemistry, Protein Engineering, Chemistry, Physics, Macromolecular sciences or close-related field
  • 5+ years of pharma/biotech industry experience in computational rational drug .
  • Demonstrated experience with ternary complex design and understanding, peptide design or protein engineering and a good understanding of peptide structure-property relationships (e.g. helicity and amphiphilicity metrics, cell penetration).
  • Demonstrated mastery of modern computational chemistry including, but not limited to, peptide folding and docking, use of co-folding foundation models, such as Boltz, structure-based design (receptor and ligand-based), scaffold hopping, docking and conformational analysis.
  • An understanding of modern drug discovery including, but not limited to, medicinal chemistry, multi-parametric optimization, molecular recognition principles, and the ability to adapt and translate these principles to stapled peptides.
  • Excellent communication and collaboration skills, with the ability to work well in a multidisciplinary environment
  • Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies
  • Expertise in one or more peptide modeling environments (e.g. ICM, Rosetta, Amber, GROMACS) and methods (enhanced sampling MD, Monte Carlo, MSM).
  • Demonstrated understanding of critical assessment of molecule-property data and predictive model quality.
  • Demonstrated understanding of experiments behind the data that can be translated to computational analysis.
  • Experience with command line modeling applications.
  • Familiarity with cloud computing environments.
  • Strong scientific programming skills (Python) in a Linux environment.
  • Experience with enterprise research informatics systems such as Dotmatics and chemical and biological data warehouses is a plus.
  • Familiarity with concepts in machine learning.
  • Familiarity with cheminformatics techniques is a plus.
  • Familiarity with use of LLMs and IDEs, such as Cursor, to enhance workflows, productivity and innovation is a plus.
  • Demonstrated use of AI tools in your current role and responsibilities is required. Advanced or innovated use of AI is a strong plus.

Core Values
Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.
  • Growth-Minded. We're inventing a new class of medicines-one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
  • In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
  • Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
  • All-In.We're All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $145,000 - $175,000 per year, depending on experience, qualifications, and internal practices. Parabilis's total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees' overall well-being.
As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

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