Student Internship in the Biostatistics department (3-4 months)

Student Internship in the Biostatistics department (3-4 months)

At Roche, we believe it’s urgent to deliver medical solutions right now - even as we develop innovation for the future. We are passionate about transforming patients’ lives. We are brave in both decision and action, we believe that good business means a better world.

As an intern you will be part of the Biostatistics team located in Basel, which consists of about 60 statisticians. As strategic partners in drug development, we apply our drug development and statistical expertise to the design of clinical development plans, clinical studies, and non-clinical experiments.

In our department we offer four different topics for internships. Your main tasks will include:

• joint multi-state time to event and longitudinal model
  • to learn and get familiar advanced survival models, especially multi-state models
  • to get familiar with Oncology response measures and longitudinal models of tumor kinetic measures over time
  • to learn about joined models of longitudinal and survival data
  • the final task is to implement a joined model, where the time to event model is a multi-state model (stable disease, response, progression, death) and the longitudinal model is a model of tumor burden over time. Programming language will be R
• sample-size for prediction model
  • Familiarize yourself with multivariable prediction models and compare the approaches to compute the sample size for a prediction model described in van Smeden et al (2018) and Riley et al (2018) for a binary endpoint through appropriate simulations
  • Work out a step-by-step example, ideally using real data, and implement in Rmarkdown. The binary and time-to-event endpoints have priority.
  • Explore the impact of a non-linear functional relationship between predictors and outcome or heterogeneity in the data,
• statistical borrowing from external controls
  • to get familiar with Oncology response measures and survival methods
  • to understand the purpose and principle of statistical borrowing methods (reduce the sample size in the standard of care by borrowing data from external sources) and get familiar with dynamical borrowing methods (“Robust Meta-Analytic Predictive Prior” (Robust MAP), “hierarchical commensurate prior approach”)
  • the final task is to implement the ”Robust MAP” approach and compare it with already implemented methods in terms of type-I error and power
  • Programming language will be preferable R
• data mining
  • to learn and get familiar with data mining methods using pooled HER2-positive early breast cancer studies
  • to work on specific questions on prediction of patient segments most likely benefiting from novel treatments respectively from de-escalation of current standard of care sing
  • advanced statistical modeling
  • to support generation of additional pooled database to investigate heterogeneity in the binary endpoint in each level with respect to hazard for continuous outcome.
  • Programming language will be R

Please state in your cover letter for which topic you apply for. At the end of your internship you are expected to summarize the outcome of your work in a written report and to give a short presentation in one of our departmental meetings.

Who you are

You are an enrolled student with a minimum of three years undergraduate training in statistics (Bachelor in Mathematics, Statistics or similar fields with a strong focus on applied statistics). Good knowledge of programming in R. Basic knowledge of Bayesian/MCMC methods and statistics is a plus. Furthermore, you have good communication skills in English.

The internships start between May and October 2019. Please clearly indicate your preferred start date and duration in your cover letter.

To be considered your application needs to include a valid certificate of enrollment, a cover letter and a CV. Non EU-EFTA citizens have to provide a certificate of mandatory internship in addition.

If you still have questions then please check our FAQs and videos on careers.roche.ch/faq.

Wer wir sind

At Roche, 94,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.

Roche is an equal opportunity employer.

Job-Fakten

• Standort Switzerland, Basel-City, Basel
• Funktion Vocational & Development Programs
• Subfunktion Internship
• Arbeitszeit Full time
• Funktionsebene Entry Level
• Art der Anstellung Temporary (Fixed Term)
• Firma/ Division Roche Pharmaceuticals
• Posted since 2019/03/18
• Job-ID 201902-106390

Kontaktieren Sie uns

Jocelyne Yates

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