What are the working arrangements and expected duration for the Internship: Agentic Workflows for Single-Cell RNA-seq Based Target Discovery role?

This position is a not disclosed, structured as a not disclosed role, with an expected duration of 6 months.

What educational background or degree level is required for the Internship: Agentic Workflows for Single-Cell RNA-seq Based Target Discovery at Roche?

Candidates are generally expected to be holding or pursuing the following degree levels: Master.

Does Roche provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

Internship: Agentic Workflows for Single-Cell RNA-seq Based Target Discovery

Q: How do I apply for the Internship: Agentic Workflows for Single-Cell RNA-seq Based Target Discovery position at Roche and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

Roche

Found 3 weeks ago

Location

Basel, Switzerland

Duration (Months)

6 Months

Time

Not disclosed

Work Mode

Not disclosed

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

3 weeks ago

Education

Master

Skills & Qualifications

Technical Skills

Python
R
Git
CI/CD pipelines
single-cell RNA-seq analysis
machine learning (ML)

Soft Skills

Excellent communication skills
passion for interdisciplinary collaboration

Job Description

We seek an exceptional individual for a 6-month internship based in Basel or Zurich, Switzerland. As part of the Computational Sciences Center of Excellence (CS CoE), you will contribute to enhancing research automation processes and cutting-edge agentic workflows supporting target identification in oncology. Your primary goal will be to identify gaps in our data and analysis ecosystem by collaborating with computational scientists working on target identification. You will evaluate new agentic workflows against existing tools and expert outputs, then partner with machine learning (ML) researchers and data experts to address key gaps. This may involve integrating new datasets, improving models, or developing complementary workflows. As a Computational Biology and Medicine (CBM) intern within Roche’s strategic CS CoE team, you will interact with experts in computational biology, ML research, and data engineering. Your work will span the strategic intersection of biology and translational science, directly contributing to Roche’s mission to improve healthcare.

Requirements

currently enrolled in a Master’s degree program in a relevant field (e.g., Computational Biology, Bioinformatics, Data Engineering, Computer Science, etc.)
Practical experience in single-cell RNA-seq analysis, including preprocessing techniques
Experience in systematically comparing tools or methods
Strong programming skills in Python and/or R and experience working with large-scale datasets
Familiarity with collaborative workflows, including proficiency in Git, CI/CD pipelines, code review processes, and reproducible analysis documentation
Excellent communication skills, with a passion for interdisciplinary collaboration
Proficiency in English (spoken and written)

AI & Machine Learning

AI Research

Languages

English

Nice to Haves

references
list of relevant publications

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