Position Snapshot
Location: Orbe (near Lausanne), Switzerland
Company: Nestlé Deep Tech Center
Act. Rate: Full-Time Act. Rate 100%
Type of contract: Internship, 6 months
Start date : June-September 2026, flexible
What we offer at Nestlé
International, diverse, equitable and inclusive work environment : Read more about our Nestlé Community
Opportunities to have an impact and contribute to your team’s success
Endless learning opportunities and enriching experiences
Strong mentorship for your professional growth
Position Summary
As a Physics Informed Machine Learning Intern, you will support the Nestlé Deep Tech Center in the development of physics‑informed and hybrid machine learning models that combine data‑driven AI with physical laws and mechanistic modeling. This role offers a unique opportunity to work at the interface of machine learning, numerical modeling, and applied physics, with a focus on physics‑informed neural networks (PINNs) and related scientific ML approaches to support industrial process modeling for ongoing projects.
The role reports directly to the Applied Machine Learning R&D Specialist, in the Artificial Intelligence group.
A Day in the Life of a Physics Informed Machine Learning Intern
* Designing and implementing physics‑informed neural network (PINN) architectures and related hybrid modeling approaches for ongoing projects
* Integrating physical constraints, governing equations, or mechanistic priors into machine learning architecture and industrial processes models
* Benchmarking scientific ML models against classical numerical or data‑driven baselines
* Analyzing results, identifying limitations, and iterating model design and training strategies
* Contributing to the integration of physics‑aware AI models into applied industrial and research use cases
What will make you successful
* Currently enrolled in or recently graduated from a master’s degree in Applied Mathematics, Applied Physics, Computer Science, or a related field
* Foundations in machine learning and numerical methods
* Familiarity with scientific machine learning concepts (e.g. PINNs, surrogate modeling, hybrid physics‑ML approaches)
* Previous experience with Python and modern ML frameworks (e.g. PyTorch / TensorFlow) in an academical or professional environment
* Ability to reason about physical systems, differential equations, or mechanistic models and translate them into ML formulations
* Curiosity and motivation to follow advances in AI‑for‑science and scientific machine learning
* English (professional working proficiency); French is a plus
Nestlé is committed to the accessibility of its recruitment process. If you require adaptation during the recruitment process, please do let us know so we can support you effectively. All information will be treated confidentially.
At Nestlé, we want to help shape a better and healthier world, inspire people to live healthier lives and deliver impact at a scale and pace that makes a difference. We do this by fostering a diverse, friendly, supportive, and collaborative environment, that creates positive disruption, embraces innovation, and empowers people and teams to win. We aim to hire friendly, respectful, inspiring people who care about the people’s lives that we touch every single day.
Be a force for good. Join Nestlé and visit us on www.nestle.com.
#J-18808-Ljbffr