Internship Modeling the Physical Dynamics of Micro-Electro-Mechanical Systems

• In this internship you will work on a challenging high-impact problem at the intersection of physics engineering and machine learning: understanding and modeling the causal physical dynamics of Micro-Electro-Mechanical Systems (MEMS). MEMS are sensor systems containing micrometer-sized mechanical structures combined with electronics. They are among the most prevalent sensor systems today due to their functionality and conveniently small size and are widely used in everyday devices such as smartphones laptops and cars.
• This internship targets highly motivated students with strong academic background who want to gain experience in applying their physics intuition and abstract thinking to real industrial systems.  
• The manufacturing of the micrometer-sized structures is a multi-stage process of high dimensionality and is susceptible to disturbances and contamination. This complexity makes controlled adaptation optimization and root-cause analysis time-intensive and often necessitates different approaches. A causal model that is a model that explains the causal relationships between system variables via a set of equations and an associated graph structure can solve the former objectives more efficiently.
• The goal of this work is for you to iteratively construct a causal model for a production subprocess. For this purpose you will first learn the fundamentals of causality and MEMS devices through provided literature. You will then use your acquired knowledge of the physical dynamics and interactions as well as their mathematical description to derive the system equations from physical principles and represent them in a graph structure iteratively validating your assumptions with domain experts. After successful model construction you benchmark popular machine learning algorithms that aim to infer causal relationships from data. Finally you summarize your work and findings in a report.
• The model construction requires a deep understanding of the physical dynamics of MEMS and their manufacturing as well as their mathematical description (e.g. differential equations). During the internship you will develop a deep understanding of MEMS and causality strengthen your modeling skills and gain experience working on open-ended industrial research problems.

Qualifications :

• Education: master studies in the field of Physics Electrical Engineering Mechanical Engineering or comparable with good gardes
• Experience and Knowledge: solid understanding of Physics Statistics Probability Theory and Differential Equations good understanding of MEMS basic Python skills basic SQL skills
• Personality and Working Practice: you are open self-driven and persistent
• Work Routine: your on-site presence is required
• Enthusiasm: fascination with physical dynamics as well as their mathematical description; comfortable working on open-ended problems without predefined solutions
• Languages: good communication skills in written and spoken English and German

Additional Information :

Start: according to prior agreement
Duration: 3 - 6 months

Requirement for this internship is the enrollment at university. Please attach your CV transcript of records enrollment certificate examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.

Need further information about the job
Anna Hunstig (Functional Department)

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Remote Work :

No

Employment Type :

Full-time