Internship Preferential Optimization in Industrial Machine Learning

Location

Magstadt | Germany

Job description

Company Description

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. Join in and feel the difference.
TheRobert Bosch GmbH is looking forward to your application!

Job Description

One can approach black-box optimization methods with the goal to reduce depending on human expert decision makers when optimizing complex systems. However, since the optimization target cannot always be quantified, preference learning i.e., preferential optimization are required to enable a synergy between human experts and machine learning systems.

• The goal of this internship is to contribute to the exploration and application of preference learning in the context of optimization for the calibration of physical systems and digital twins.
• You will acquire an overview of existing preferential optimization methods.
• Moreover, you will identify and help to solve the gaps between the state of the art and the requirements at hand.
• Last but not least collaborative software development in a joint code base to evaluate different approaches will be also part of your responsibilities.

Qualifications

• Education: Master studies in the field of Computer Science, Mathematics, Cognitive Science or comparable
• Experience and Knowledge: in machine learning, preferably (Bayesian) optimization or preference learning is beneficial as well as proven software development skills, in particular with Python
• Languages: good English

Additional Information

Start: according to prior agreement
Duration: 4 - 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?
Lukas Grossberger (Functional Department)
+49 152 57908357

#LI-DNI

Summary

• Type: Full-time
• Function: Science

Job tags

Salary