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Scientist II, Computer Aided Drug Design

Cambridge, MA   ·   Full-Time

Reports To: Director, Medicinal Chemistry

Company Overview

METiS Therapeutics Inc is a biotechnology company with a unique technology platform that has the potential to drive best-in class drug assets in a wide range of therapeutic areas. Through the integration of machine learning, quantum simulation, and high-throughput experimentation, we enable scientists to rapidly, comprehensively, and intelligently develop novel drug candidates. METiS is founded by an enthusiastic team of MIT researchers and serial entrepreneurs. Our cross-disciplinary expertise and deep industry experiences allow METiS to harness AI to boldly deliver revolutionary therapies for patients with serious diseases.


We are looking for an experienced computational chemist with robust knowledge and proven skill sets in molecular modeling. A key element of her/him is a strong interest in data- and hypothesis- driven drug discovery by applying state-of-the-art computational chemistry methods, including structure- and ligand-based design, virtual screening, free energy simulation, and molecular dynamics. As a key member of the team, she/he is expected to work independently and demonstrate scientific leadership and creativity within a multi-disciplinary environment.


  • Work with a high degree of independence to carry out structure and ligand-based design and data analysis

  • Support all aspects of the company’s computational chemistry efforts targeting multiple cellular pathways/mechanism and indications

  • Develop and implement computational chemistry approaches to design and triage compound ideas

  • Closely collaborate and communicate with medicinal chemists and biologists to understand current issues and provide effective solutions

  • Proactively propose strategies for effective use of computational chemistry to accelerate hit-to-lead and lead optimization toward clinical candidates

  • Create machine learning/AI strategies through communication with global colleagues and exploit the methodologies to implement a more effective design environment

  • Participate in interdisciplinary teams and external collaborations

  • Work in a fast-paced/small-team environment that is growing and evolving and which requires regular reprioritization of projects while adhering to timelines and achievement of deliverables

Minimum Qualifications

  • Ph.D. in computational chemistry or related discipline with 2+ years in the biotech/pharmaceutical industry.

  • A proven record of scientific leadership and innovation as demonstrated by publications, presentations, and / or patents

  • Practical experience in structure-based drug design, including docking, homology modeling, molecular dynamics simulation, and free energy calculation; ligand-based drug design, including pharmacophore modeling, QSAR, pharmacophore- or shape-based database searching, combinatorial library design, and target focused library construction

  • Robust understanding of Linux command line is required in addition to strong programming/scripting capabilities (Python, R, Schrodinger/OEChem and machine learning API’s, including Scikit-learn and Tensorflow)

  • Practical experience with cloud computing environments such as AWS, Microsoft Azure, or GCloud

  • Familiarity with Collaborative Drug Discovery or Dotmatics software a plus

  • Ability to multitask and support multiple projects simultaneously

  • Experience managing external collaborations, including CRO’s

  • Excellent communication and organizational skills are required

  • Must be willing to relocate full time to Greater Boston Area within 6 months of start date

RECRUITING & STAFFING AGENCIES: METiS Therapeutics does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to METiS or its employees is strictly prohibited unless contacted directly by METiS recruiting team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of METiS, and METiS will not owe any referral or other fees with respect thereto.

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