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Developing machine learning methods for organoid phenotyping and high-throughput screening at biotech firm focused on healthcare access. Ongoing Master's or PhD studies in a technical field required. Expert mentorship provided.
Requirements
- Master’s degree, ongoing masters, or PhD studies in related technical field
- Proficiency in Python, ML frameworks, and modern software engineering tools
- Excellent communication and data visualization skills
- Drive to tackle biomedical problems and enthusiasm for ML applications
- Experience applying ML to biomedical data or open-source contributions (Nice-to-have)
Tasks
- Develop ML methods for organoid phenotyping
- Design high-throughput screening techniques
- Analyze rich, high-content datasets
- Apply state-of-the-art machine learning methods
- Create predictive models for perturbation screens
- Integrate multimodal imaging and genomics data
- Build foundational models for organoid phenotyping
- Develop predictive methods for cell fate engineering
- Discover causal mechanisms from perturbation experiments
- Implement active learning for iterative experimental design
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- JAX
- PyTorch
- Git
- CI/CD
- scRNA/ATAC-seq
Benefits
Informal Culture
- Personal expression culture
- Open dialogue environment
Other Benefits
- Scientific community membership
Mentorship & Coaching
- Expert mentorship
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Developing machine learning methods for organoid phenotyping and high-throughput screening at biotech firm focused on healthcare access. Ongoing Master's or PhD studies in a technical field required. Expert mentorship provided.
Requirements
- Master’s degree, ongoing masters, or PhD studies in related technical field
- Proficiency in Python, ML frameworks, and modern software engineering tools
- Excellent communication and data visualization skills
- Drive to tackle biomedical problems and enthusiasm for ML applications
- Experience applying ML to biomedical data or open-source contributions (Nice-to-have)
Tasks
- Develop ML methods for organoid phenotyping
- Design high-throughput screening techniques
- Analyze rich, high-content datasets
- Apply state-of-the-art machine learning methods
- Create predictive models for perturbation screens
- Integrate multimodal imaging and genomics data
- Build foundational models for organoid phenotyping
- Develop predictive methods for cell fate engineering
- Discover causal mechanisms from perturbation experiments
- Implement active learning for iterative experimental design
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- JAX
- PyTorch
- Git
- CI/CD
- scRNA/ATAC-seq
Benefits
Informal Culture
- Personal expression culture
- Open dialogue environment
Other Benefits
- Scientific community membership
Mentorship & Coaching
- Expert mentorship
About the Company
Roche
Industry
Pharmaceuticals
Description
The company is dedicated to advancing science and ensuring access to healthcare for everyone.
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