Internship – Machine Learning And Molecular Simulation For Functional Antibody Characterisation

Roche UK

Basel, Switzerland
Not specified; not specified; not specified
Master's degree within 12 months or phd enrollment
Experience with amber openmm gromacs plumed
Proficiency in pytorch neural network building
The role involves developing novel data-driven machine learning methods to characterize antibody structural ensembles for drug discovery

Job Summary

  • The role involves developing novel data-driven machine learning methods to characterize antibody structural ensembles for drug discovery.
  • Candidates will deploy these methods at scale using high-performance computing resources to generate large synthetic datasets.
  • This is a full-time 6-month on-site internship located in Basel, Switzerland, requiring continuous university enrollment.

Matching Summary

The role involves developing novel data-driven machine learning methods to characterize antibody structural ensembles for drug discovery.

Salary

Not specified; Not specified; Not specified

Skills & Requirements

Must-have

  • Master's degree within 12 months or PhD enrollment
  • Experience with Amber OpenMM Gromacs Plumed
  • Proficiency in PyTorch neural network building
  • High performance computing environment fluency
  • Python programming for complex pipelines

Nice-to-have

  • Collaboration across Basel New York San Francisco
  • Contribution to scientific publications
  • Presentation of results at internal venues
  • Flexible project goals based on candidate profile

Key Requirements

  • Recent Master graduate or current PhD student
  • Mandatory university enrollment for internship duration
  • Non-EU/EFTA citizens need mandatory internship certificate

Work Rights

Non-EU/EFTA citizens must provide mandatory internship certificate from university

Tailored Resume

Cover Letter