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Intern in Machine Learning for Antibody-Antigen Complex Scoring(m/w/x)
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.
Anforderungen
- 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)
Aufgaben
- 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
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Machine Learning
- geometric and spatial representation learning
- deep learning frameworks
- PyTorch
- Structural Biology
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Intern in Machine Learning for Antibody-Antigen Complex Scoring(m/w/x)
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.
Anforderungen
- 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)
Aufgaben
- 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
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Machine Learning
- geometric and spatial representation learning
- deep learning frameworks
- PyTorch
- Structural Biology
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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