Roche
Intern (Machine Learning – RNA Splicing)(m/w/x)
Full-timeInternshipOn-site
Basel
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RORoche
Intern in Machine Learning for Antibody-Antigen Complex Scoring(m/w/x)
Basel
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Developing multi-modal scoring functions for antibody-antigen complexes, bridging geometric deep learning and physics. Master's student in technical field with ML and PyTorch experience required. Research initiatives toward scientific publication.
Requirements
- Master’s student in technical field (Bioinformatics, Computer Science, Physics, or related quantitative discipline)
- Strong foundational knowledge of machine learning (geometric and spatial representation learning focus)
- Hands-on experience with modern deep learning frameworks (PyTorch preferred)
- Familiarity with ML application in Structural Biology
- Excellent communication and collaboration skills
- Proficiency in English (strong verbal and written communication)
Tasks
- Develop a multi-modal scoring function
- Bridge geometric deep learning and physics-based energy approximations
- Create and implement methods to rank antibody-antigen complexes
- Collaborate with international, cross-functional teams
- Drive research initiatives toward scientific publication
- Merge computational techniques with drug discovery efforts
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Machine Learning
- geometric and spatial representation learning
- deep learning frameworks
- PyTorch
- Structural Biology
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Roche and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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RORoche
Intern in Machine Learning for Antibody-Antigen Complex Scoring(m/w/x)
Basel
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Developing multi-modal scoring functions for antibody-antigen complexes, bridging geometric deep learning and physics. Master's student in technical field with ML and PyTorch experience required. Research initiatives toward scientific publication.
Requirements
- Master’s student in technical field (Bioinformatics, Computer Science, Physics, or related quantitative discipline)
- Strong foundational knowledge of machine learning (geometric and spatial representation learning focus)
- Hands-on experience with modern deep learning frameworks (PyTorch preferred)
- Familiarity with ML application in Structural Biology
- Excellent communication and collaboration skills
- Proficiency in English (strong verbal and written communication)
Tasks
- Develop a multi-modal scoring function
- Bridge geometric deep learning and physics-based energy approximations
- Create and implement methods to rank antibody-antigen complexes
- Collaborate with international, cross-functional teams
- Drive research initiatives toward scientific publication
- Merge computational techniques with drug discovery efforts
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Machine Learning
- geometric and spatial representation learning
- deep learning frameworks
- PyTorch
- Structural Biology
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Roche and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Roche
Industry
Pharmaceuticals
Description
The company is dedicated to advancing science and ensuring access to healthcare for everyone.
Not a perfect match?
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