PhD student internship in single-cell RNA-seq-based machine learning

At Roche, we believe it is urgent to deliver medical solutions right now – even as we develop innovations 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.

The Bioinformatics and Exploratory Data Analysis (BEDA) team is looking for a PhD student with experience in machine learning and single-cell RNA sequencing (scRNA-seq) data analysis to develop in silico models of perturbation-induced changes. The successful candidate will be integrated in our diverse team of Bioinformaticians and Biostatisticians, and gain exposure to various Roche Pharma Research and Early Development (pRED) projects. Our group’s mission is to collaborate with teams across all Disease Translational Areas (oncology, neuroscience, immunology, ophthalmology, infectious diseases) providing state-of-the-art support in data integration, data analysis and data interpretation. As part of ongoing digitalisation efforts, this novel internship programme dedicated to PhD students that wish to gain industry experience was created, focusing on innovative approaches in the digital space.

Key responsibilities
The main focus of this position is the evaluation and implementation of machine learning methods for out-of-sample prediction of treatment effects in scRNA-seq data. The successful candidate’s tasks will also include data mining of public and internal scRNA-seq data, code and data management, evaluation, visualization and presentation of the results.


  • Ongoing PhD studies in Bioinformatics, biostatistics, computational biology, informatics or similar field
  • Experience in single-cell RNA-seq data analysis
  • Experience in machine learning
  • Proficiency in Python and at preferably one other programming language (preferably R)
  • Ability to work in international teams
  • Good communication and presentation skills
  • Fluency in English

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