Roche Postdoctoral Fellowship, Machine Learning/Statistics/Modeling in the Clinical Pharmacology D.

Basel, Canton of Basel-Stadt (CH)
By Agreement
February 19 2018
Position Type
Organization Type

Job facts 

The Roche Postdoctoral Fellowship (RPF) program is aimed at supporting excellent young scientists focusing on collaborative R&D projects between Roche and international academic institutions. Both internal Roche and academic experts will mentor you, and you will have the potential to perform hands on research in both environments.

Within Roche pharma Research and Early Development (pRED), the Clinical Pharmacology department is committed to enable the selection of safe and effective dose, route and regimen for every patient by applying the principles of quantitative pharmacology throughout a molecule’s life-cycle. As a part of Clinical Pharmacology, the Disease Modeling group supports the decision making process in the respective disease therapeutic area through the development of empirical and/or mechanistically-based drug disease models which integrate disease pathophysiology, drug target information and clinical data.

In this project, you will develop and apply novel integrative machine learning framework to identify prognostic and predictive markers of outcomes measured longitudinally in rheumatoid arthritis clinical trials. This framework will be based on statistical concepts such as Bayesian hierarchical models, multi-view/multi-task machine learning methods to make use of clinical variables, biomarkers and –omics datasets (such as transcriptomics, proteomics, metabolomics and immunomics), collected at baseline.

Who you are 

You’re someone who wants to influence your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. Where a job title is not considered the final definition of who you are, but the starting point.

You hold a PhD in the fields of machine learning, biostatistics, computational biology, applied mathematics or mathematical modeling applied to life sciences (obtained within the last 4 years), with strong computational and coding skills and proficiency in at least one high level scientific language (such as R/MATLAB/Python/Julia). Additionally, you bring the following skills and expertise:

Please include a detailed CV with a publication list, contact information for at least two references, a research statement and a cover letter with your expected date of availability.

  • Strong analytic skills, with ability to understand and develop  mathematical/statistical methods and to translate them into a computational algorithm;
  • Expertise in either exploratory data analysis (including building/evaluating statistical models from data) or developing mathematical models from first-principle using domain expertise knowledge;
  • Experience in analyzing longitudinal clinical data using statistical methods (e.g. linear or non-linear mixed effect models) or mathematical modeling (e.g.  system biology/pharmacology and PK/PD modeling);
  • Practice of applying machine learning methods to analyze –omics data;Knowledge of Bayesian methodology (in particular hierarchical models), Bayesian computation (e.g. MCMC, HMC, Variational Bayes Approximation);
  • Experience with Bayesian software such as Stan/Jags/WinBUGS;
  • Familiarity with machine learning methods such as multi-view/multi-task concepts;
  • Experience in implementing computationally efficient algorithms in languages such as C/C++/Fortran/Java;
  • A background in pharmacology, life sciences or medicine and a clear interest in clinical research;
  • Flexibility and capability to work independently;
  • Excellent communication and writing skills in English as well as a proven track record of publishing in peer reviewed journals.

Who we are

Basel is the headquarters of the Roche Group and one of its most important centres of pharmaceutical research. Over 8,500 people from approximately 90 countries work in Basel, which is one of Roche`s largest sites.

Roche is an equal opportunity employer. 

HR contact person: Luanda De Sa Pereira; Phone: +41 61 687 8884

Link to apply: