Alle Stellen

Seeking a Machine Learning Scientist to lead the development and application of advanced AI technologies for designing nucleic acid-based medicines. Drive sequence optimisation, collaborate with experimentalists, and translate biological questions into predictive models. Ideal for candidates with a strong background in machine learning and molecular biology.

Tasks

  • Lead the development and application of next-generation AI technologies for designing DNA and RNA sequences for nucleic acid-based medicines.
  • Build, train, and fine-tune machine learning algorithms to optimize nucleic acid-based medicines for active portfolio projects.
  • Design candidate sequence libraries for lab-in-the-loop optimization cycles, analyze experimental readouts (e.g., MPRA, NGS), and iteratively update designs.
  • Collaborate cross-functionally with wet-lab scientists and project leads to understand therapeutic constraints and tailor design algorithms accordingly.
  • Present technical findings, candidate designs, and model performance metrics to cross-functional team members and stakeholders.
  • Stay current with advancements in biological sequence modeling and nucleic acid therapeutics to bring state-of-the-art methods into the pipeline.
  • Contribute to scientific publications.

Requirements

  • Ph.D. in a quantitative discipline (Bioinformatics, Computational Biology, Computer Science, Machine learning, or a related field) with 0-4 years of post-doctoral or industry experience.
  • Demonstrated research impact at the interface of machine learning and molecular biology, evidenced by publications in top-tier journals or ML conferences.
  • Strong Python programming skills and proficiency in deep learning frameworks such as PyTorch.
  • Hands-on experience developing, training, or fine-tuning sequence-to-function models for biological molecules (preferably DNA/RNA).
  • Excellent communication skills in English, with the ability to speak to both computational and experimental scientists.
  • Preferred: Prior experience applying machine learning in a biotech, pharma, or industry setting.
  • Preferred: Domain knowledge in nucleic acid-based therapeutics (e.g., mRNA design, AAV capsid/promoter engineering, cell therapy vectors).
  • Preferred: Experience with advanced ML frameworks relevant to sequence design, such as generative modeling (diffusion, autoregressive sequence models, masked language models), active learning, model interpretability, or uncertainty quantification.
  • Preferred: Familiarity with high-throughput functional genomics data processing (e.g., MPRA, RNA-seq, ribosome profiling).
Bist du Teil dieses Unternehmens?

Dieses Unternehmensprofil wurde automatisch erstellt. Wenn du für Roche Schweiz arbeitest, kannst du das Profil jetzt beanspruchen und verifizieren – kostenlos und in wenigen Minuten.

Verifizierte Profile erhalten ein Siegel und können ihre Seite, Stellen und Bewerbungen direkt verwalten.
Über uns
Roche ist ein international tätiges Schweizer Pharma- und Diagnostikunternehmen mit Sitz in Basel und entwickelt, produziert und vertreibt Medikamente sowie diagnostische Lösungen. Das Unternehmen ist in den Bereichen Pharma und Diagnostik tätig und fokussiert sich auf Forschung und Innovation in verschiedenen Therapiegebieten wie Onkologie, Neurologie und Infektionskrankheiten. Roche ist weltweit aktiv und zählt zu den führenden Unternehmen im Gesundheitsbereich.
Das Team

AI Biology & Translation (AIBT) is part of the Computational Sciences Center of Excellence (CS-CoE) and develops and applies cutting-edge artificial intelligence to accelerate biomedical discovery and translational science. The team integrates expertise in machine learning, computational biology, and software engineering to enable researchers to generate new biological insights and transform research across Genentech & Roche. Collaboration with stakeholders in Cell Therapy, Gene Therapy, and Vaccine Oncology is central to the team's diverse projects.

Ähnliche Stellen