Master Thesis in Foundation Model Compression Methods
Master Thesis in Foundation Model Compression Methods
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
The research team at the Bosch Center for Artificial Intelligence (BCAI) provides the opportunity for students in machine learning computer vision or a related field to complete their Masters thesis with us. At BCAI we build the foundation to generate real world impact through cuttingedge research focusing on data/computeeEicient and generalizable AI. We design and implement AI for smart connected and autonomous technologies across Bosch business sectors.
- During your time at Bosch you will get the chance to develop and implement novel algorithms and evaluate them on multimodal open and Bosch datasets.
- Together with BCAI researchers you will perform original research theoretical investigations and aim to publish at top ML conferences.
- The goal is to define the topic that fits within the scope of a Masters thesis. Possible research areas include foundation model compression via knowledge distillation or dynamic compute to enable hardwareEicient neural networks.
Qualifications :
- Education: Master studies in the field of Computer Science Mathematics Physics or comparable with good grades
- Experience and Knowledge: in machine learning deep learning natural language understanding robotics or computer vision from previous internships work personal projects and/or lab work; ideally good publication record with at least one publication at tier1 conferences in the field of machine learning robotics natural language processing or computer vision (e.g. NeurIPS ICML ACL CVPR ICLR etc.) as well as excellent and proven programming skills particularly in Python and PyTorch/TensorFlow
- Personality and Working Practice: a teamminded and analytical individual with a structured way of working
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
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.
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 Schott (Functional Department)
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
