Senior Scientist II (Computational Chemistry)

Exelixis; Alameda (CA); Presencial; USD 149.000 - 188.000; Tempo integral

Benefícios oferecidos por esta vaga

401(k) plan with company contributions

Comprehensive medical, dental, and/or视

Resumo da vaga

Exelixis is seeking a Senior Scientist II in Computational Chemistry to advance drug discovery through physics-based modeling, cheminformatics, and data-driven workflows. You will integrate molecular dynamics, docking, and ML to generate testable design hypotheses and prioritize compounds in collaboration with medicinal chemists and biologists.

The role emphasizes developing reliable computational pipelines, applying validation methods, and communicating results to cross-functional teams in a

Qualificações

• PhD/MS/BS with extensive experience in computational chemistry or cheminformatics.

Responsabilidades

• Apply ligand- and structure-based computational methods to support small-molecule discovery programs.

Conhecimentos

Molecular modeling

Python

Cheminformatics

Machine learning

Structure-based design

Formação

PhD in Computational Chemistry or related

MS in related discipline with industry experience

BS in related discipline with extensive experience

Equivalent education/experience

Ferramentas

RDKit

OpenMM

GROMACS

AMBER

Descrição da vaga

SUMMARY:

We are seeking a Senior Scientist II in Computational Chemistry to join our small-molecule discovery organization. The successful candidate will apply physics-based molecular modeling, cheminformatics, and data-driven methods to advance drug discovery programs. This role is designed for a scientist with a strong foundation in computational chemistry and a particular interest in connecting molecular simulation with cheminformatics, workflow automation, and practical machine learning. The individual will contribute to molecular dynamics, free-energy calculations, structure-based design, and compound prioritization while developing reliable computational and machine learning workflows that increase the impact of predictive methods across discovery portfolio. Strong scientific judgment, programming ability, communication, and collaboration skills are essential. The successful candidate will work closely with medicinal chemists, structural biologists, biologists, pharmacologists, and bioinformatics scientists in a fast-paced, interdisciplinary research environment.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Apply ligand- and structure-based computational methods to support small-molecule discovery programs.
• Plan, execute, analyze, and communicate molecular dynamics simulations and free-energy calculations for compound prioritization and molecular design.
• Apply molecular docking, protein-ligand interaction analysis, conformational analysis, similarity searching, and other computational approaches to generate experimentally testable design hypotheses.
• Use cheminformatics methods to analyze compound collections, explore structure-activity relationships, assess chemical diversity, and support virtual library design and prioritization.
• Evaluate and apply appropriate machine-learning methods for molecular property or activity prediction, in combination with physics-based modeling and experimental data.
• Assess machine-learning model performance and applicability using scientifically appropriate validation methods, and clearly communicate limitations and uncertainty. Apply and develop cheminformatics and machine learning models to enable predictive analytics across the pipeline
• Contribute to virtual screening campaigns using structure-based, ligand-based, and fragment-based approaches.
• Integrate computational results into collaborative discovery platforms and project workflows, including tools such as LiveDesign and Spotfire.
• Collaborate closely with medicinal chemists, structural biologists, biologists, pharmacologists, and other project stakeholders to interpret data and influence compound-design decisions.
• Present computational analyses, recommendations, assumptions, and uncertainties clearly to scientific project teams.
• Stay current with emerging methods in molecular simulation, free-energy calculations, cheminformatics, machine learning, and computer-aided drug design.
• Contribute to the continued development of computational chemistry capabilities and a predict-first culture within the discovery organization.

EDUCATION & EXPERIENCE:

• Bachelor's degree in related discipline and a minimum of 9 years of relevant experience; or,
• Master's degree in related discipline and a minimum of 7 years of relevant experience; or,
• PhD in Computational Chemistry, Cheminformatics or related discipline, with at least 2 years of relevant experience in the biotechnology or pharmaceutical industry; or,
• Equivalent combination of education and experience.

KNOWLEDGE & SKILLS:

• Strong foundation in molecular modeling and the physical principles governing protein-ligand interactions. Hands-on experience with one or more structure-based drug-design methods, such as molecular docking, molecular dynamics, free-energy calculations, conformational analysis, or protein-ligand interaction analysis.
• Proficiency in Python for scientific computing, data analysis, or computational workflow development.
• Working knowledge of cheminformatics concepts, such as molecular representations, fingerprints, molecular descriptors, similarity searching, substructure searching, clustering, or compound-library analysis.
• Familiarity with open-source cheminformatics or molecular-modeling tools, such as RDKit, OpenMM, GROMACS, AMBER, or comparable platforms.
• Ability to analyze computational and experimental data critically and translate results into clear, testable molecular-design hypotheses. Understanding of structure-activity relationships and the physicochemical characteristics relevant to small-molecule drug discovery.
• Strong written, oral, and presentation communication skills. Ability to work effectively in cross-functional teams and communicate computational findings to scientists from different technical backgrounds.
• Scientific curiosity and willingness to learn new methods as program needs and technologies evolve.

ADDITIONAL SKILLS & ABILITIES:

• Strategic thinker with a passion for applying computational & ML approaches to solve practical problems in drug discovery
• Collaborative team player, able to work seamlessly across disciplines
• Proactive, innovative, and adaptable in a fast-paced environment
• Strong balance of technical depth and project impact orientation
• Strong written, oral, and presentation communication skills

If you have a disability and need an accommodation in relation to the recruiting process, please email us at: [e-mail]

Location: Alameda, CARange for this position: $149,000 - $188,000The base pay offered will take into account job-related knowledge, skills, experience and internal equity, among other factors.In addition to the base salary, as part of our Total Rewards program, Exelixis offers comprehensive employee benefits package, including a 401k plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts. Employees are also eligible for a discretionary annual bonus program, or if field sales staff, a sales-based incentive plan. Exelixis also offers employees the opportunity to purchase company stock, and receive long-term incentives, 15 accrued vacation days in their first year, 17 paid holidays including a company-wide winter shutdown in December, and up to 10 sick days throughout the calendar year.

WORKING CONDITIONS:

Our office is a modern space that fosters collaboration and creativity. Teams work closely together, sharing ideas and solutions in a supportive atmosphere. We provide all necessary equipment, including dual monitors and ergonomic chairs, to ensure a comfortable workspace.

DISCLAIMER:

The preceding job description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.