GSK

Associate Director, QSP Modelling

GSK$157K — $262K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in relevant field like Applied Mathematics or Systems Biology.
  • 2+ years in Pharma/Biomedical industry with QSP experience.
  • Strong grasp of mathematical modeling, numerical methods, and ODEs.
  • Proficiency in modeling languages (e.g., MATLAB, Python).

Responsibilities

  • Develop QSP models to assess disease mechanisms and drug candidates.
  • Collaborate with cross-functional teams to guide research programs.
  • Lead QSP expertise in disease areas and relevant experimental methodologies.
  • Serve as point-of-contact for QSP modeling in project teams.
  • Utilize advanced mathematical tools to analyze drug-target interactions.
  • Interpret complex datasets considering disease pathways and mechanisms.
  • Explore QSP synergies with AI/ML and genetic analysis.

Benefits

  • Comprehensive health care and insurance for employees and family.
  • Retirement benefits to support future savings.
  • Generous paid holidays and vacation days.
  • Paid leave for caregivers and parental responsibilities.
  • Access to a long-term incentive program.
Full Job Description

Job Title: Associate Director, Quantitative Systems Pharmacology

Location: Upper Providence, PA or Cambridge, MA

We are seeking an Associate Director level, Quantitative Systems Pharmacology Disease Lead for our Drug Metabolism and Pharmacokinetics (DMPK) department.

Quantitative Systems Pharmacology (QSP) is a discipline that uses quantitative and mechanistic mathematical disease models to enhance the robustness and quality of decision-making from early research through clinical development.  DMPK is a science-driven organization that drives the translational understanding of drug disposition and quantitative pharmacology to deliver transformational medicines with our partners.

We are seeking a highly motivated individual to develop and apply QSP models within discovery to aid in the prioritization, selection, understanding, and optimization of promising treatments for a variety of diseases and therapeutic areas. The successful candidate will be responsible for integrating data and knowledge in a highly collaborative and multi-disciplinary environment to develop a deeper understanding of physiological systems and disease mechanisms with the goal of influencing target prioritization, modality evaluation, and delivering molecules with transformational potential into the clinic.

Role Responsibilities:

This role will provide YOU the opportunity to lead key activities to progress YOUR career, these responsibilities include some of the following.

  • Build and utilize QSP models of biological, physiological, and pathophysiological processes to evaluate a disease, its pathways and progression, as well as drug candidates and treatment modalities
  • Work in close collaboration with biologists, clinicians, clinical pharmacologists, QSP and nonclinical modelers, and other partner line colleagues to inform research programs and improve our understanding of disease mechanisms
  • Serve as a disease-area QSP lead, possessing or developing expertise in disease pathophysiology, biomarkers, clinical endpoints, as well as in key experimental methodologies and data
  • Serve as QSP modeling & simulation point-of-contact on project teams to solve challenging problems in drug research; contribute to preclinical study design and mechanistic interpretation of data
  • Develop and/or utilize state-of-the-art mathematical tools to gain insight into causal relationships between individual components of system-level and drug-level responses of drug-target-biomarker-disease-patient interaction
  • Analyze and interpret complex data sets in the context of disease mechanisms and pathways
  • Explore new opportunities to combine QSP with other analytical approaches and build synergies through collaboration with computational groups working in areas related to human genetics, functional genomics, and AI/ML
  • Perform scientific rigor and biological suitability assessment of QSP models and methodologies through applying a context-driven verification & validation process (reviewing QSP model goals, assumptions, methodology, model code, model outputs, uncertainty quantification)

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

  • PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods
  • 2 or more years of experience in Pharma Life Science Biomedical industry developing and applying QSP approaches to drug discovery or development programs
  • Experience working with the theory, principles, statistical aspects of mathematical modeling and simulation, including numerical methods, parameter estimation/optimization, ordinary differential equations (ODEs), and how these can be applied in the development of complex models of biological pathways and systems
  • Computational experience with one or more modeling and simulation packages or programming languages (e.g., MATLAB, SimBiology, Julia, Python, C/C++)

Preferred Qualifications:

If you have the following characteristics, it would be a plus:
 

  • Solid biological understanding of immunology and previous experience in applying mechanistic modeling to metabolic, inflammatory, or fibrotic diseases
  • Experience summarizing, condensing, and translating outcomes of modeling and simulation analyses into knowledge and insights that can be clearly understood by project teams
  • Experience working with Large Language Models (LLMs) and Agentic AI (e.g., tool use and multi-agent orchestration)
  • Demonstrated collaborative ways of working and ability to work successfully in matrix teams
  • Ability to effectively communicate and interact with key stakeholders, medical professionals and senior leadership
  • Ability to learn new areas of biological sciences and build on solid foundation of quantitative skills
  • Experience with the application of scientific machine learning (SciML) approaches to mechanistic modeling
  • Experience integrating omics and/or other multi-modal data with mechanistic models

#LI-GSK


Skills

Artificial Intelligence (AI), Computational Sciences, Computer Programming, Data Analysis, Data Management, Data Modeling, Data Science, Predictive Modeling, Statistical Models

 

 

• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $157,575 to $262,625. The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.

Please visit  GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

About GSK

GSK is a British multinational pharmaceutical company that specializes in researching, developing, and manufacturing a wide range of prescription drugs and vaccines. The company was founded in 2000 through the merger of Glaxo Wellcome and SmithKline Beecham. GSK's products are used to treat a variety of conditions including respiratory diseases, HIV/AIDS, and cancer. The company operates in over 150 countries and has a workforce of over 99,000 employees. GSK is headquartered in Brentford, England and is listed on the London Stock Exchange and the New York Stock Exchange.
Learn more about GSK
Size
90,096 employees
Market Cap
$71.6 billion
Industry
Net Income
$5.7 billion
Founded
1929
5 Year Trend
+4.1%
Revenue
$34 billion
NASDAQ

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