data-science

Bosch Group

<div><section><div><p></p><h2>Company Description</h2></div><div><p><strong>At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. </strong><strong>Join in and feel the difference.</strong></p><p>The Robert Bosch GmbH<em> </em>is looking forward to your application!</p></div></section><section><div><p></p><h2>Job Description</h2></div><div><p>In contemporary virtual engineering processes, the critical role of reliable simulation models cannot be overstated. The challenge persists in constructing an accurate model for a dynamic system based on empirical data.</p><ul><li>In the scope of this thesis, you will help bridging the gap between simulation model and data, using modern optimization methods and information measures on the data.</li><li>Typically, these models are expressed through systems of differential equations, dependent on parameters requiring optimization through alignment with empirical data. Starting with a comprehensive examination of an existing adjoint optimization method, you will explore the interplay between the unique identifiability of parameters and the gradient landscape.</li><li>Based on this, suitable excitation functions to enhance the identifiability of parameters shall be derived from you.</li><li>Furthermore, your responsibilities will encompass the development and implementation of proprietary algorithms, simulative investigations on example data, and the demonstration of results using vehicle models.</li></ul></div></section><section><div><p></p><h2>Qualifications</h2></div><div><ul><li><strong>Education:</strong> Master studies in the field of Mathematics, Control Engineering, Physics, Mechanical Engineering or comparable</li><li><strong>Experience and Knowledge:</strong> in programming (preferable in Python), optimization as well as ordinary differential equations</li><li><strong>Personality and Working Practice:</strong> creative and communicative team player with a structured and independent way of working</li><li><strong>Enthusiasm:</strong> for programming, solving real-world mathematical problems and fusion of data and modeling</li><li><strong>Languages:</strong> German or English</li></ul></div></section><section><div><p></p><h2>Additional Information</h2></div><div><p><strong>Start:</strong> according to prior agreement<br> <strong>Duration:</strong> 6 months</p><p>Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.</p><p>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.</p><p><strong>Need further information about the job?</strong><br> Dr. Nicola Henkelmann (Business Department)<br> +49 711 811 54916</p><p><br> #LI-DNI</p></div></section></div>

Master Thesis Reliable Simulation Models - Combining Data and Expert Knowledge

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