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PhD Student - Machine Learning for Biosystems Engineering(m/w/x)
Research on organoid engineering and drug discovery, analyzing high-content datasets from perturbation experiments at a healthcare-focused research institution. Master's student or recent graduate in computational biology or related technical field, with Python and modern ML frameworks proficiency required. Interdisciplinary collaboration with experimental scientists.
Anforderungen
- Master’s student or recent graduate in computational biology, computer science, machine learning, bioinformatics, or related technical field
- Proficiency in Python and modern ML frameworks
- Knowledge of modern software engineering tools and methodologies
- Strong fundamentals in linear algebra, statistics, and genomics ML
- Excellent communication skills in English
- Skill in data visualization and communicating complex findings
- Drive to tackle biomedical problems and translate ML methods
- Track record of relevant publications or open-source contributions
- Experience applying ML methods to biomedical data
- Experience in single-cell genomics data analysis and computer vision
- Experience working with experimental collaborators
Aufgaben
- Lead a research project on organoid engineering
- Develop computational methods for drug discovery
- Apply machine learning to human biology questions
- Analyze high-content datasets from perturbation experiments
- Collaborate with experimental scientists to shape research
- Create predictive ML methods for high-throughput screens
- Integrate multimodal imaging and genomics data
- Build foundational models for organoid phenotyping
- Develop predictive methods for cell fate engineering
- Discover causal mechanisms from high-content experiments
- Implement active learning for iterative experimental design
- Publish research findings in academic journals
- Contribute to open-source computational tools
- Advance next-generation human model systems
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- JAX
- PyTorch
- TensorFlow
- GitHub
- GitLab
- CI/CD
Benefits
Abwechslungsreiche Aufgaben
- Interdisciplinary work environment
Lockere Unternehmenskultur
- Personal expression and dialogue
- Inclusive and respectful culture
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PhD Student - Machine Learning for Biosystems Engineering(m/w/x)
Research on organoid engineering and drug discovery, analyzing high-content datasets from perturbation experiments at a healthcare-focused research institution. Master's student or recent graduate in computational biology or related technical field, with Python and modern ML frameworks proficiency required. Interdisciplinary collaboration with experimental scientists.
Anforderungen
- Master’s student or recent graduate in computational biology, computer science, machine learning, bioinformatics, or related technical field
- Proficiency in Python and modern ML frameworks
- Knowledge of modern software engineering tools and methodologies
- Strong fundamentals in linear algebra, statistics, and genomics ML
- Excellent communication skills in English
- Skill in data visualization and communicating complex findings
- Drive to tackle biomedical problems and translate ML methods
- Track record of relevant publications or open-source contributions
- Experience applying ML methods to biomedical data
- Experience in single-cell genomics data analysis and computer vision
- Experience working with experimental collaborators
Aufgaben
- Lead a research project on organoid engineering
- Develop computational methods for drug discovery
- Apply machine learning to human biology questions
- Analyze high-content datasets from perturbation experiments
- Collaborate with experimental scientists to shape research
- Create predictive ML methods for high-throughput screens
- Integrate multimodal imaging and genomics data
- Build foundational models for organoid phenotyping
- Develop predictive methods for cell fate engineering
- Discover causal mechanisms from high-content experiments
- Implement active learning for iterative experimental design
- Publish research findings in academic journals
- Contribute to open-source computational tools
- Advance next-generation human model systems
Berufserfahrung
- ca. 1 - 4 Jahre
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- JAX
- PyTorch
- TensorFlow
- GitHub
- GitLab
- CI/CD
Benefits
Abwechslungsreiche Aufgaben
- Interdisciplinary work environment
Lockere Unternehmenskultur
- Personal expression and dialogue
- Inclusive and respectful culture
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Roche
Branche
Healthcare
Beschreibung
The company is dedicated to advancing science and ensuring access to healthcare for everyone.
Noch nicht perfekt?
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