Who we are

At Roche, 90,000 people across 150 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. The headquarters in Basel is one of Roche's largest sites, over 8,500 people from approximately 90 countries work at Roche Basel. Favoured by its geographic location in the heart of Europe, the Basel area is one of the most dynamic economic regions in Switzerland - a great place to live and work.

The Position

We are seeking a highly motivated postdoctoral fellow with a strong background in computational biology and machine learning to join our cross-functional spatial transcriptomics team in the Predictive Modeling & Data Analytics and Pathology chapters, part of Roche Pharma Research and Early Development (pRED) - Pharmaceutical Sciences. The University of Heidelberg, Germany and the Swiss Institute of Bioinformatics, Lausanne, Switzerland are Roche's academic partners for this Postdoctoral Fellowship.

This position is sponsored by the Roche Postdoctoral Fellowship Programme. The RPF Programme has the ambition to build and maintain the Scientific Leadership of the future and to provide leading Roche scientists with the opportunity to collaborate with talented postdoctoral researchers, and leading academic research groups, from around the world. One of the key aims is to advance basic science and technologies that will be published in top-rated, peer-reviewed scientific journals, if necessary preceded by priority patent applications.

The duration of the RPF project is initially set for two years, with the possibility of extension for a third year. You will be based in Basel. 

In this position, you will 

process spatial transcriptomics (ST) datasets from mouse and human tissues with defined morphological structures and high relevance for toxicology readouts. You will develop integrative analysis approaches of morphological patterns, cell identity and gene expression using deep learning methods.  The output will deliver precise organ structure annotations and further provide cell type composition, spatial cell clustering, pathway activities and cell communication readouts. You will further help generate a ST database that provides an invaluable reference to assess compound-associated changes and to evaluate their translational relevance for patients.

You will be working in a multidisciplinary team in close collaboration with pathologists, bioinformaticians and genomics specialists. In addition, you will be mentored by two academic co-supervisors who will provide input and guidance throughout the project. 

Your impact:

You will support the analysis of ST data in toxicology related projects. 

You will integrate morphological features and gene expression profiles at the tissue level through ML-based methods to precisely annotate organ structures. 

You will help our team to develop and store the results from the two previous points into a database. 

You will publish the main results of your work in peer reviewed journals. 

Your profile:

PhD in computational biology, bioinformatics, statistics, cheminformatics or related fields with experience in an academic or industry setting in the area of machine learning and/or omics data analysis. 

Proficiency in working with bioinformatics and statistical tools and methods as well as a strong background in machine learning and statistics. 

Proficient in Python, R or an equivalent programming language

Experience with digital pathology is beneficial but not required

You exhibit a growth mindset. You ask for feedback and act on it. You embrace opportunities to gain new skills and perspectives and provide honest feedback to others to help them grow. 

You have very good interpersonal and communication skills, are able to build good working relationships, and are an outstanding teammate. Your experience and investigative attitude allow you to work independently, to design, perform, and interpret experiments, and to embark on new scientific methodologies.

You have been actively engaged in scientific research continuously since your PhD and ready to start an RPF postdoctoral activity no later than 5 years after the PhD 

Excellent communication skills in English

When does it start?

The start date of this fellowship is September 2022, or on availability. Please clearly indicate your preferred starting date on your motivation letter.

Please include a CV, motivation letter, a publication list and references in your application.

Do you know what Roche stands for? Roche embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.

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

More information about the RPF Programme: https://www.roche.com/careers/workplaces/wp_research/the-roche-postdoctoral-fellowship-programme.htm