12 meilleures offres (python, vaud) (à pourvoir)

Intern, Protein Design
Adaptyv —Lausanne, VD
- 100%
- Travail hybride
- Niveau Doctorat
- Python
AI Workflows Engineer
Neural Concept —Lausanne, VD
- 100%
- Travail hybride
- CAD
- Python
Spécialiste Business Intelligence
Ansam Group —Le Vaud, VD
- Travail hybride
- Informatique
- Anglais
- SQL
Head of Finance
Adaptyv —Lausanne, VD
- 100%
- Travail hybride
- Droit du travail et de l'emploi
- SQL
- Nettoyage
P2621 – (Senior) Pharmacometrician
Debiopharm —Lausanne, VD
- Niveau Doctorat
- Anglais
- Sens de l'organisation
Elektrokonstrukteur:in/Elektroingenieur:in (Schaltplan- & Schemaentwicklung)
cross-ING AG —Yverdon-les-Bains, VD
- 100%
- Travail hybride
- CAD
- Anglais
- C++
GNC Engineer
Harmattan AI —Lausanne, VD
- 100%
- Niveau Master
- C++
- Python
P2621 - (Senior) Pharmacometrician
Debiopharm —Lausanne, VD
- Travail hybride
- Niveau Doctorat
- Anglais
- Sens de l'organisation
Postuler rapidement
AI Research Scientist
Giotto.ai —Lausanne, VD
- 100%
- Travail hybride
- Recherche
- Niveau Master
- Compétences en communication
Postuler rapidement
Machine Learning Engineer
Giotto.ai —Lausanne, VD
- 100%
- Télétravail
- Niveau Doctorat
- Python
Postuler rapidement
Senior Scientist II, Data Science (CompBio for Translation and Biomarkers in Cardio-Renal-Metabolics)
HAYA Therapeutics —Epalinges, VD
- 100%
- Niveau Doctorat
- Python
Postuler rapidement
Senior Research Engineer / Research Scientist - Post-Training, Reinforcement Learning & Training Systems
Giotto.ai —Lausanne, VD
- 100%
- Travail hybride
- Niveau Doctorat
- Python
Postuler rapidement
4 h

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Intern, Protein Design

Adaptyv
Lausanne, VD

Soumettre votre candidature

Détails de l'emploi

100%

Qualifications

Niveau Doctorat
Python

Description complète du poste

Adaptyv is building an automated lab that lets AI agents run biology experiments.

We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world.

We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today.

Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development.

We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.

Responsibilities

Run and benchmark open-source protein design methods on real Adaptyv targets, validated against experimental data from our wet lab.
Design binders for internal R&D campaigns, and track experimental performance across success rate, hit rate, kinetics, and developability.
Build computational tooling around the design pipeline: structure prediction, filtering, and ranking, to triage large design pools down to candidates for synthesis and characterization.
Support the technical side of our open competitions and hackathons: drafting track briefs, supporting participants, judging submissions, and writing up results.
Contribute open data, blog posts, designer spotlights, and method comparisons to Proteinbase.

Qualifications

Currently enrolled in a Master's, PhD, or final-year undergraduate programme in computational biology, machine learning, biochemistry, biophysics, bioengineering, or a related field.
Hands-on experience with at least one modern open-source protein design method.
Strong Python and PyTorch skills. Comfortable working with biology data formats.
A working understanding of binding kinetics and developability that extends beyond in silico metrics, with a healthy scepticism of computational scores as ground truth.
Bonus: prior open-source contributions to a protein design repository, a strong showing in a public design competition, or a published blog post or paper.

Duration: 3-6 months. Paid.

Location: Remote, or on-site in Lausanne. Lausanne is preferred if you want lab access and the full design-build-test-learn exposure.

Application deadline

We are reviewing applicants on a rolling basis. Please include a link to a GitHub repository, competition submission, blog post, or other concrete work demonstrating your approach to protein design.

Application deadline

We are reviewing applicants on a rolling basis.

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python emplois - vaud

Intern, Protein Design

AI Workflows Engineer

Spécialiste Business Intelligence

Head of Finance

P2621 – (Senior) Pharmacometrician

Elektrokonstrukteur:in/Elektroingenieur:in (Schaltplan- & Schemaentwicklung)

GNC Engineer

P2621 - (Senior) Pharmacometrician

AI Research Scientist

Machine Learning Engineer

Senior Scientist II, Data Science (CompBio for Translation and Biomarkers in Cardio-Renal-Metabolics)

Senior Research Engineer / Research Scientist - Post-Training, Reinforcement Learning & Training Systems

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : python (vaud)

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