Senior Manager, Quantitative Systems Pharmacology
US - CA - Foster City, Estados Unidos
Full Time Senior-level / Expert USD 169K - 219K
Gilead Sciences
Gilead Sciences, a biopharma company, achieves bold ambitions to help make the world a healthier place, leading in HIV, liver disease, cancer & inflammation.At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.
We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.
Job Description
As a Quantitative Systems Pharmacologist, your main role will be in scoping, developing and applying mechanistic disease progression and systems pharmacology models at Gilead. In this role, you will have opportunities to inform multiple aspects of the drug development process including optimizing drug candidates through mechanistic simulation, dose/target optimization, identifying biomarkers for clinical programs, and recommending doses, regimens and subpopulations for inclusion into clinical trial design. Further areas of focus include reverse translation of clinical findings and development of platform models to support combinations and inform portfolio development strategy.
Responsibilities
- Develop QSP models for one or more disease areas incorporating available in-house and published data
- Regularly communicate with cross-functional teams to develop and periodically update modeling strategy to ensure timely and impactful execution of modeling goals
- Present model findings to clinical teams and incorporate feedback as needed
- Provide expert guidance across teams as needed
- Contribute to regulatory documents using the appropriate level of documentation and reproducibility
- Maintain accurate records including data, assumptions, parameter values, model changes, etc. while developing models
- Proactively identify opportunities for applying or adapting QSP models to support portfolio and project needs
- Develop and maintain reusable software tools as needed to support and streamline QSP efforts
- Author manuscripts describing model development and findings as needed
- Present modeling work externally at conferences and working groups
- Mentor junior scientists on areas related to QSP, if needed
Required Experience and Skills:
- Proficiency in mathematical and computational skills needed for QSP modeling work, including but not limited to ordinary differential equations, linear algebra, statistics, optimization, and parameter inference
- Relevant education in computational/systems biology, physics, engineering, or computer science
- Proficiency in relevant software and programming languages which may include python, R, C++, Julia, or MATLAB and MATLAB SimBiology (preferred)
- Basic understanding of molecular and cellular biology including for example concepts from immunology, oncology, virology, cellular signaling, etc.
- Basic understanding of concepts of drug development
- 3+ years of relevant experience and a PhD or PharmD degree
Preferred skills:
- Experience with QSP software and Bioinformatics tools for informing QSP models
- Familiarity with other modeling techniques: ABMs, PDEs, SDEs, SSA, graph theoretical methods, information theoretical methods, Boolean networks, etc.
- Familiarity with methodologies for Bayesian parameter inference
- Expert knowledge in one or more relevant disease areas (oncology, inflammation, virology)
- Machine learning and AI expertise (LLMs, classical methods for regression or classification)
- Application development experience (e.g. in MATLAB AppDesigner)
- Experience with pharmacokinetic/pharmacodynamic modeling in small molecules and biologics or other pharmacometric modeling experience
- Familiarity with drug development and clinical pharmacology in a pharmaceutical company setting
For additional benefits information, visit:
https://www.gilead.com/careers/compensation-benefits-and-wellbeing
* Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
For jobs in the United States:
Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact ApplicantAccommodations@gilead.com for assistance.
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Tags: Bayesian Bioinformatics Biology Classification Computer Science Engineering Julia Linear algebra LLMs Machine Learning Matlab ML models Pharma PhD Physics Python R Statistics
Perks/benefits: Career development Conferences Equity / stock options Health care Insurance Medical leave Salary bonus Transparency
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