Data Science Internship in Exercise Multi-Omics

Job Description Summary

Contribute to systems-level investigation of exercise biology by conducting quantitative analyses of high-dimensional, multi-modal omics datasets.

Job Description

Physical exercise is a powerful intervention, beneficial for almost all tissues and organs. We set out to dissect the molecular mechanisms underlying the health promoting effects of exercise, leveraging high resolution, multi-omics data to identify novel therapeutic entry points for diseases of aging.

The DARe (Diseases of Aging and Regenerative Medicine) Translational and Data Science team is seeking an enthusiastic intern in data science who will contribute to systems-level analyses of exercise biology. This is an excellent opportunity to gain insights into the role of data science in fast moving and cutting-edge drug discovery programs.

Expected start date: immediate

Duration: 6 months

Location: Campus Basel

Your responsibilities: 

• Quantitatively explore and model multi-tissue/organ transcriptomics (bulk & single-cell RNA-seq) and proteomics data, aimed at integrating in-house data with publicly available data to answer key scientific questions.. 
• Collaborate with multidisciplinary teams and communicate your findings to other data scientists and/or scientists within the wider DARe research group.
• Contribute to the implementation of tools and algorithms enabling efficient analysis of biological data.

What you’ll bring to the role: 

• Recent MSc graduate or currently enrolled in an MSc program, in computational biology, bioinformatics or data science (some biology knowledge is strongly preferred).

• Fluency in English, both spoken and written. 

• Proficient in R programming, with good knowledge of statistical data modelling and experience with data wrangling, data cleaning and visualization (R Tidyverse, RMarkdown, RShiny).

• Hands-on experience in some type of omics data analysis (with preference for RNAseq or single-cell RNAseq).,

• Some experience working in Unix/Linux and HPC environment.

• High learning agility, solution-based approach to problem-solving, developed scientific curiosity and a desire to make a difference for patients.

• Strong interpersonal and communication skills, recognized as a team player and ready to take the initiative.

• Optional: knowledge in exercise biology; Experience with Knowledge Graphs and graph-based network analyses.

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to all

individuals. If, because of a medical condition or disability, you need a reasonable

accommodation for any part of the recruitment process, or in order to receive more detailed

information about the essential functions of a position, please send an e-mail to

diversity.inclusion_ch@novartis.com and let us know the nature of your request and your

contact information. Please include the job requisition number in your message.

Skills Desired

Summary

• Location: Basel (City)
• Type: Full time