Internship in computer vision and AI at IUNA AI Systems GmbH focusing on data preparation for AI models and collaboration with ML engineers. Join a deep tech startup specializing in AI - based image processing.
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Onsite Internship – Training and Deploying AI/ML Protein Abundance Models
Posted last week
About the role
- Intern in Computational Sciences Center of Excellence supporting R&D project focused on AI/ML in drug development. Leveraging AI and data for innovative medicines at Roche.
Responsibilities
- Support a translational R&D project focused on inferring protein molecule numbers across human tissues.
- Deliver an MVP “predictability map” that clarifies when RNA is a reliable proxy for protein abundance—and when it isn’t.
- Collaborate with experts in ML research, computational biology and data engineering.
- Leverage pharma-scale infrastructure to bridge the gap between AI innovation and significant biological discoveries.
- Set up robust data management and a deployment pathway so scientists can run inference reproducibly.
- Enable MVP release workflows (v0.1 → v0.x) by producing stable, queryable tables/exports and clear “what changed” release notes.
- Operationalize Machine Learning Algorithms: Leverage your understanding of machine learning to operationalize existing algorithms.
Requirements
- Bachelor’s or Master’s degree within the past 12 months, or currently enrolled in a Master’s or PhD program in a relevant field (preferably in Computer Science, Data engineering, Bioinformatics, Computational Biology)
- Solid programming skills in Python (and/or R) and confidence working with data at scale.
- Familiarity with data pipelines, reproducibility, and collaborative workflows (Git, CI/CD, code review, documentation)
- Familiarity with containers (Docker) and cloud/HPC workflows.
- Experience with data modelling in MongoDB or other NoSQL databases
- Prior experience in mass spectroscopy readouts, protein abundance, or -omics data and common identifiers/mappings (gene/protein IDs, ontologies)
- Familiarity with Kubernetes or other deployment orchestration
- Experience using and developing REST APIs (e.g. using FastAPI, Plumber)
- Strong communication skills and enjoyment of cross-functional teamwork
- Proficiency in English (written, spoken).
Benefits
- Professional development opportunities
- Flexible working hours
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