PhD - Online Machine Learning
- Robert-Bosch-Campus 1, Renningen, Germany
- Legal Entity: Robert Bosch GmbH
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Most of probabilistic machine learning models are trained in a batch setting, i.e. learning in an offline manner using pre-collected data, while employing excessive computational resources. In order to take full advantage of a learning approach, online learning is an absolute necessity, as it allows the adaption to changes in the system dynamics and environment. Furthermore, an offline training data set will never suffice for most systems with a large number of degrees of freedom and, thus, online learning is essential, if the sampled data leads to new parts of the state-space. In this research work, we want to explore novel online learning techniques appropriate for industrial setting.
- We are looking for exceptionally talented PhD students who are looking to tackle difficult research problems that have relevance to real world applications.
- During the course of the thesis you will tackle research questions in the field of Bayesian machine learning in an online setting.
- Master of Science in natural sciences, e.g. Machine Learning, Computer Science, Mathematics, Physics, Cybernetics
- (Very) good grades
- Knowledge of and practical experience in Machine Learning is a plus
- Strong knowledge of Python or Matlab
- Independence and strong intrinisic motivation
- Strong English language skills
Duration: 3 years
The final PhD topic is subject to your university.
Need support during your application ?
Kevin Heiner (Human Resources)
+49 711 811 12223
Need further information about the job?
The-Duy Nguyen-Tuong (Business Department)
+49 711 811 49408