The Nestl茅 Deep Tech Center is where we develop and evaluate cutting-edge technologies to accelerate Nestl茅鈥檚 global innovation mission and shape the future of food at scale. Leveraging聽advanced robotics and sensor聽technologies,聽AI, machine learning and digital聽twins, we聽are聽driving smarter manufacturing, delivering breakthrough consumer experiences, and maximizing our聽research and innovation capabilities.聽 Every project here connects you to Nestl茅鈥檚 purpose: unlocking the power of food to enhance quality of life for individuals, families, communities, and the planet, today and for generations to come.
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Based in Orbe, Switzerland, and complemented by our Deep Tech Hub in Shenzhen, China, our state-of-the-art facility fosters a collaborative working environment, with聽creative spaces, rapid鈥憄rototyping labs, automated kitchens, and pilot plants, so innovation moves fast from concept to reality.
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Ready to build technology that matters? Join us and be a force for good!
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Position Snapshot** **
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Location: Orbe (near Lausanne), Switzerland
Company: Nestl茅 Deep Tech Center
Act. Rate: Full-Time Act. Rate 100%
Type of contract: Internship, 6 months
Start date : June-September 2026, flexible
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What we offer at Nestl茅
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International, diverse, equitable and inclusive work environment : Read more about our Nestl茅 Community
Opportunities to have an impact and contribute to your team鈥檚 success
Endless learning opportunities and enriching experiences
Strong mentorship for your professional growth
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**Position Summary聽 **
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As a Physics Informed Machine Learning Intern, you will support the Nestl茅 Deep Tech Center in the development of physics鈥慽nformed and hybrid machine learning models that combine data鈥慸riven 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鈥慽nformed neural networks (PINNs) and related scientific ML approaches to support industrial process modeling for ongoing projects.
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The role reports directly to the Applied Machine Learning R&D Specialist, in the Artificial Intelligence group.
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A Day in the Life of a Physics Informed Machine Learning Intern
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Designing and implementing physics鈥慽nformed neural network (PINN) architectures and related hybrid modeling approaches for ongoing projects
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Integrating physical constraints, governing equations, or mechanistic priors into machine learning architecture and industrial processes models
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Benchmarking scientific ML models against classical numerical or data鈥慸riven baselines
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Analyzing results, identifying limitations, and iterating model design and training strategies
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Contributing to the integration of physics鈥慳ware AI models into applied industrial and research use cases
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What will make you successful
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Currently enrolled in or recently graduated from a master鈥檚 degree in Applied Mathematics, Applied Physics, Computer Science, or a related field
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Foundations in machine learning and numerical methods
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Familiarity with scientific machine learning concepts (e.g. PINNs, surrogate modeling, hybrid physics鈥慚L approaches)
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Previous experience with Python and modern ML frameworks (e.g. PyTorch / TensorFlow) in an academical or professional environment
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Ability to reason about physical systems, differential equations, or mechanistic models and translate them into ML formulations
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Curiosity and motivation to follow advances in AI鈥慺or鈥憇cience and scientific machine learning
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English (professional working proficiency); French is a plus
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Nestl茅 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.
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At Nestl茅, 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鈥檚 lives that we touch every single day.
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Be a force for good. Join Nestl茅 and visit us on www.nestle.com .