Quantitative Systems Pharmacology & Toxicology

6 days left

Cambridge, England, Cambridgeshire
23 Feb 2021
09 Mar 2021
R & D , Pharmacology
Full Time
Contract Type
Experience Level

At AstraZeneca, we're not afraid to do things differently! We're building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we're opening up new ways to work, pioneering cutting edge methods and bringing unexpected teams together.

The Systems Medicine group is seeking a systems modelling scientist passionate about using advanced mathematical modelling and computational sciences to develop and use mechanistic models of pharmacology and toxicology.

Working in a dynamic, multidisciplinary environment the successful candidate will develop, calibrate and use Quantitative Systems Pharmacology (QSP) and/or Toxicology (QST) models to integrate mechanistic knowledge and data on disease pathophysiology and drug pharmacology which can be linked with clinical outcomes.

This position is an exciting opportunity to impact critical decision making in the progression of new drugs. The successful scientist will be working on a highly stimulating and collaborative environment with biologists, clinicians, pharmacometricians, translational medicine scientists, Machine Learning and systems modelers.


  • Create, expand or refine mathematical models to address drug-discovery and development questions
  • Conduct literature reviews to identify suitable mechanistic elements, interactions, rate constants and existing models for incorporation into the modelling solution.
  • Align QSP model deliverables with safety, clinical pharmacology and development plans
  • Review, analyse and prepare available data for modelling purposes
  • Reflect on the best modelling approach to address questions and deliverables
  • Contribute to the design, execution and interpretation of clinical studies
  • Test and participate to the adoption of existing or new modelling platforms
  • Review modelling works with colleagues as appropriate, insuring high quality standards
  • Stay informed with emerging literature and science in modelling and simulation sciences.

Primary skills and qualifications

  • PhD or similar degree in chemical, mechanical or biomedical engineering, physics, applied mathematics, scientific computing or related field
  • Hand-on knowledge of modelling with ODEs, Statistical and/or Machine Learning modelling, inference, model parametrization, model training and testing
  • Excellent understanding of theory, principles and statistical aspects of advanced mathematical modelling and simulation, including numerical methods, parametrization and ODEs.
  • Experience with modelling and data analysis tools and languages such as R and Matlab or Python.
  • Self-directed, independent and highly-motivated researcher who excels in a collaborative, multi-disciplinary environment.
  • Excellent oral and written communication skills and the ability to interact effectively with scientists in other subject areas with a positive and collaborative attitude
  • Ability to learn new areas of biological sciences and build on solid foundation of quantitative skills to develop models
  • Ability to keep up to date with and propose the implementation of scientific and technological developments, notably in the area of Systems Pharmacology and Toxicology
  • Desire to interact across clinical development teams with specialists from different pre-clinical and clinical functional areas

Preferred Skills And Qualifications (these would be a plus)

  • Industry or postdoctoral experience in building, validating and using predictive mathematical models.
  • Aptitude and experience to influence decisions and experimental design by using available data and appropriate modelling solutions
  • Knowledge of models of biological pathways/systems to support translational and/or clinical research.
  • Good understanding of the basic principles of pharmacokinetics and pharmacodynamics.
  • Experience in linking QSP/QST models with drug pharmacokinetics to predict safe and efficacious doses
  • Experience with specific population PK, PKPD and joint longitudinal modelling tools such as Monolix, NONMEM, Torsten, Nlmixr or IQRtool.
  • Experience with Bayesian inference using STAN
  • Familiarity with the challenges of drug discovery and forward thinking with respect to the general application of mathematical models in discovery and development
  • Evidence of identifying, developing, and applying innovative solutions to scientific and technological problems faced in systems and predictive modelling

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Salary: Competitive

So, what's next?

Are you already imagining yourself joining us? Good, because we can't wait to hear from you!

Welcome with your application; CV and cover letter, no later than 9th March 2021

For more information please contact:

Additional information

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