Thesis hybrid modeling for powertrain functions
neues Angebot (05/03/2020)
stellenbeschreibung
Job Description Company Description Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch. The Robert Bosch GmbH is looking forward to your application! Job Description A hybrid approach combining machine learning methods with physical models with preserves the physical information, while still improving the flexibility and precision of the model. This type of individually tailored hybrid approach requires a combination of strong domain knowledge and data science expertise, leading to more robust semi-interpretable models and increased physical understanding* Help Shape The Future
:you are responsible for the creative and pro-active implementation of new machine learning concepts and algorithms combining data-driven and physics-based models. * take responsibility:
prototypical algorithm implementations and benchmarking on real-world data sets will be part of your thesis. * experience cooperation:
take an active role in technical discussions and creation of new ideas together with the domain experts and the machine learning research team. qualifications * education:
master studies in the field of machine learning, mathematics, physics, computer science, engineering or related fields with excellent grades * personality and working practice:
analytical, structured, innovative and conceptually thinking character * experience and knowledge:
excellent theoretical, it and analytical skills proven by top course grades, general knowledge of machine learning. prior knowledge of numerical simulations and thermodynamics is a plus. programming experience in python and matlab. * languages:
fluent in english and good in german written and spoken additional information start:
according to prior agreement duration:
6 months requirement for this thesis is the enrollment at university. please attach a motivation letter, your cv, transcript of records, examination regulations and if indicated a valid work and residence permit. need further information about the job? wael hilali (business department) +49 711 811 92959 qualifications:
education:
master studies in the field of machine learning, mathematics, physics, computer science, engineering or related fields with excellent grades personality and working practice:
analytical, structured, innovative and conceptually thinking character experience and knowledge:
excellent theoretical, it and analytical skills proven by top course grades, general knowledge of machine learning. prior knowledge of numerical simulations and thermodynamics is a plus. programming experience in python and matlab. languages:
fluent in english and good in german written and spoken responsibilities:
a hybrid approach combining machine learning methods with physical models with preserves the physical information, while still improving the flexibility and precision of the model. this type of individually tailored hybrid approach requires a combination of strong domain knowledge and data science expertise, leading to more robust semi-interpretable models and increased physical understanding. help shape the future:
you are responsible for the creative and pro-active implementation of new machine learning concepts and algorithms combining data-driven and physics-based models. take responsibility:
prototypical algorithm implementations and benchmarking on real-world data sets will be part of your thesis. experience cooperation:
take an active role in technical discussions and creation of new ideas together with the domain experts and the machine learning research team.
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