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Intern (Machine Learning – RNA Splicing)(m/w/x)
Developing reproducible pipelines for sequence scoring and integrating state-of-the-art splicing prediction models at a global healthcare research organization. Master's degree in Computational Biology or related field, plus strong Python skills essential. Direct contribution to therapeutic sequence design with cutting-edge predictive models.
Anforderungen
- Master's degree (past 12 months) or current Master's/PhD enrollment in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related field
- Strong Python programming skills
- Experience with ML frameworks (PyTorch or TensorFlow)
- Familiarity with RNA and DNA biology
- Experience with reproducible research workflows (Git, HPC/cloud)
- Strong communication skills
- English proficiency (written and spoken)
- Experience with deep learning for biological sequences
- Knowledge of RNA splicing biology
- Familiarity with AAV gene therapy or RNA therapeutics
- Track record of scientific software development
- Experience operationalizing ML models
- Experience building lightweight user-facing tools
- Non EU/EFTA student university enrollment for internship duration
- Internship as mandatory curriculum part for Non EU/EFTA students
Aufgaben
- Integrate and benchmark state-of-the-art splicing prediction models
- Develop reproducible pipelines for sequence scoring
- Support model-guided design of therapeutic sequence constructs
- Support prioritization of therapeutic sequence constructs
- Contribute to structured benchmarking against experimental data
- Contribute to documentation for researcher adoption
- Contribute to usability for researcher adoption
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- TensorFlow
- Git
- HPC
- Cloud environments
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Intern (Machine Learning – RNA Splicing)(m/w/x)
Developing reproducible pipelines for sequence scoring and integrating state-of-the-art splicing prediction models at a global healthcare research organization. Master's degree in Computational Biology or related field, plus strong Python skills essential. Direct contribution to therapeutic sequence design with cutting-edge predictive models.
Anforderungen
- Master's degree (past 12 months) or current Master's/PhD enrollment in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related field
- Strong Python programming skills
- Experience with ML frameworks (PyTorch or TensorFlow)
- Familiarity with RNA and DNA biology
- Experience with reproducible research workflows (Git, HPC/cloud)
- Strong communication skills
- English proficiency (written and spoken)
- Experience with deep learning for biological sequences
- Knowledge of RNA splicing biology
- Familiarity with AAV gene therapy or RNA therapeutics
- Track record of scientific software development
- Experience operationalizing ML models
- Experience building lightweight user-facing tools
- Non EU/EFTA student university enrollment for internship duration
- Internship as mandatory curriculum part for Non EU/EFTA students
Aufgaben
- Integrate and benchmark state-of-the-art splicing prediction models
- Develop reproducible pipelines for sequence scoring
- Support model-guided design of therapeutic sequence constructs
- Support prioritization of therapeutic sequence constructs
- Contribute to structured benchmarking against experimental data
- Contribute to documentation for researcher adoption
- Contribute to usability for researcher adoption
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- PyTorch
- TensorFlow
- Git
- HPC
- Cloud environments
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Roche
Branche
Pharmaceuticals
Beschreibung
The company is dedicated to advancing science and ensuring access to healthcare for everyone.
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