Consultant Scientist, Computer Aided Drug Design (CADD)

Psivant Therapeutics, Inc.

$150K — $185K *
Pharmaceuticals & Biotech
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • PhD in computational chemistry, organic/physical chemistry, physics, or closely related field.
  • Minimum of 5 years CADD or related biotech/pharma experience, with a track record in small molecule drug discovery.
  • Expertise in physics-based, AI/ML, and generative computational approaches to drug discovery.
  • Strong communication and collaboration skills in cross-functional teams.
  • Excellent organizational skills with attention to detail and enthusiasm for learning new technologies.

Responsibilities

  • Design small molecule therapeutics using various data sources for drug discovery projects.
  • Integrate computational tools and medicinal chemistry knowledge throughout all project stages.
  • Collaborate with the computational development team to synchronize project priorities.
  • Enhance and improve internal applications based on physics-based simulation capabilities.
  • Train and mentor team members on modeling and AI/ML concepts to meet project needs.

Benefits

  • Dynamic, multidisciplinary team environment focused on innovative medicine development.
  • Opportunity to collaborate across functions including medicinal chemistry and structural biology.
  • Role in advancing cutting-edge computational technologies for drug discovery.
  • Potential to influence drug development pipelines from concept to clinic.
Full Job Description
PsiThera is seeking a consultant computational medicinal chemist with expertise in drug discovery, molecular simulations and AI/ML to join our dynamic, multidisciplinary team. Our science, our team, and our mission are focused on applying advanced computational technologies to progress a pipeline of innovative medicines for patients. We are looking for a self-motivated individual who thrives in a fast-paced, highly collaborative environment that integrates computational and wet lab capabilities to drive our programs to the clinic. The ideal candidate will utilize advanced computational strategies across all stages of drug discovery, including hit identification, hit-to-lead and lead optimization. In addition, a successful candidate will have a demonstrable pharma/biotech industry record using computational methods to advance drug discovery projects, analyze simulation and AI/ML results, derive actionable hypotheses and effectively communicate findings to the team. This individual will report to the Senior Director of CADD and collaborate closely across functions including experimental medicinal chemistry, structural biology, and application engineering teams to provide actionable insights and strategic guidance.

Key Responsibilities

  • Design small molecule (and related modality) therapeutics using structural/simulation/ML/assay data, ensuring alignment with the requirements and timelines of our drug discovery projects, and leading computational analysis and design activities on cross-functional projects.
  • Integrate knowledge of relevant computational tools and approaches, as well as key aspects of medicinal chemistry and compound property optimization, for all project stages from target selection and druggability analysis to clinical candidate nomination.
  • Collaborate with the computational development team to align priorities between platform application development and R&D projects.
  • Develop modifications and drive improvements in internal applications, building on our internal physics-based simulation capabilities and assessment of fidelity and accuracy of calculations.
  • Train and mentor team members across the organization to build understanding of modeling and AI/ML concepts and how they address project team needs.


Requirements

  • PhD in computational chemistry, organic or physical chemistry, physics, or a closely related field
  • Minimum of 5 years computer-aided drug design (CADD) or related biotech/pharma experience, with expertise accelerating small molecule drug discovery projects from target tractability and hit identification, through lead optimization (demonstrated by peer reviewed publications and inventorship status on patent applications)
  • Demonstrated experience and understanding of physics-based, AI/ML, and generative computational approaches to drug discovery
  • 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


Additional Qualifications

  • Proficiency in scientific programming (e.g. Python, R, C++)
  • Proficiency in molecular simulation packages (e.g. AMBER, OpenMM, NAMD, Gromacs)
  • Proficiency in data science and machine learning tools (e.g. scikit-learn, pytorch)
  • Experience mentoring interns, co-ops, and junior scientists


$150,000 - $185,000 a year

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