Roche
Intern in Machine Learning for Antibody-Antigen Complex Scoring(m/w/x)
VollzeitPraktikumnur vor Ort
Basel
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Dein persönlicher KI-Karriere-Agent
RORoche
Internship – Machine Learning and Molecular Simulation for Functional Antibody Characterisation(m/w/x)
Basel
VollzeitPraktikumVor Ort
AI/ML
Nejo KI-Zusammenfassung
Developing novel data-driven sampling methods for antibody structural ensembles. Master's or PhD in a technical field with simulation software and neural network experience required. HPC environments and Python proficiency needed.
Anforderungen
- Recent Master's graduate (within 12 months) or enrolled PhD student in Bioinformatics, Computational Biology, Computational Physics, Computer Science, Statistics, Applied Mathematics, or related technical field
- Theoretical knowledge and practical experience with enhanced sampling methods or other simulation techniques and their application to protein systems
- Extensive practical experience with at least one simulation software suite (e.g. Amber, OpenMM, Gromacs, Plumed)
- Some experience with building and training neural networks within at least one DL framework (preferably pytorch), keen to build models from scratch or adapt architectures from literature
- Fluent in high performance computing (HPC) environments and comfortable with at least one programming language (ideally Python) for building complex orchestrating pipelines
- Excellent communication and interpersonal skills
- Maintained enrollment at a university for the full duration of the internship
- Non-EU/EFTA citizens must provide a certificate from the university stating that an internship is mandatory and must be continuously enrolled for the whole duration of the internship
Aufgaben
- Develop novel data-driven sampling methods
- Evaluate machine learning-based sampling techniques
- Characterize antibody structural ensembles accurately
- Generate large-scale synthetic datasets
- Orchestrate efficient use of compute resources
- Contribute to real drug-discovery projects
- Collaborate with teams in Basel, New York, and San Francisco
- Drive or contribute to publications
- Present results at internal and external venues
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – fließend
Tools & Technologien
- Amber
- OpenMM
- Gromacs
- Plumed
- pytorch
- Python
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Roche erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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Internship – Machine Learning and Molecular Simulation for Functional Antibody Characterisation(m/w/x)
Basel
VollzeitPraktikumVor Ort
AI/ML
Nejo KI-Zusammenfassung
Developing novel data-driven sampling methods for antibody structural ensembles. Master's or PhD in a technical field with simulation software and neural network experience required. HPC environments and Python proficiency needed.
Anforderungen
- Recent Master's graduate (within 12 months) or enrolled PhD student in Bioinformatics, Computational Biology, Computational Physics, Computer Science, Statistics, Applied Mathematics, or related technical field
- Theoretical knowledge and practical experience with enhanced sampling methods or other simulation techniques and their application to protein systems
- Extensive practical experience with at least one simulation software suite (e.g. Amber, OpenMM, Gromacs, Plumed)
- Some experience with building and training neural networks within at least one DL framework (preferably pytorch), keen to build models from scratch or adapt architectures from literature
- Fluent in high performance computing (HPC) environments and comfortable with at least one programming language (ideally Python) for building complex orchestrating pipelines
- Excellent communication and interpersonal skills
- Maintained enrollment at a university for the full duration of the internship
- Non-EU/EFTA citizens must provide a certificate from the university stating that an internship is mandatory and must be continuously enrolled for the whole duration of the internship
Aufgaben
- Develop novel data-driven sampling methods
- Evaluate machine learning-based sampling techniques
- Characterize antibody structural ensembles accurately
- Generate large-scale synthetic datasets
- Orchestrate efficient use of compute resources
- Contribute to real drug-discovery projects
- Collaborate with teams in Basel, New York, and San Francisco
- Drive or contribute to publications
- Present results at internal and external venues
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – fließend
Tools & Technologien
- Amber
- OpenMM
- Gromacs
- Plumed
- pytorch
- Python
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Roche erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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.
Noch nicht perfekt?
- Roche
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