PhD - in Multi-Modal Deep Learning Models
- Robert-Bosch-Campus 1, 71272 Renningen, Germany
- Legal Entity: Robert Bosch GmbH
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!
- Your contribution to something big: Today, a lot of knowledge is hidden in large amounts of unstructured data, especially images and text data. In this context, multi-modal Machine Learning models, especially deep learning approaches, can be beneficial to extract knowledge and store it in a structured format.
- Create something new: You develop and implement novel multi-modal models with a focus on text and image data. Important research questions are robust representations of multiple modalities in the same vector space, the extraction of knowledge from text and images as well as an effective usage of given background knowledge for different tasks.
- Help shape the future: You take part at technical discussions and develop new ideas within the research team at BCAI and with domain experts from various fields within Bosch Corporate Research.
- Take responsibility: You do original research and publish in top-tier journals and at top-tier conferences.
- Education: Excellent Degree (Master) in computer science (or related field)
- Personality: Team player and self-motivated, inter-cultural and cross-domain proficiency
- Working Practice: Independently and within a team environment
- Experience and Knowledge: Proven programming skills (e.g. Python/Java/C++), Machine Learning experience
- Languages: Fluent in English (spoken and academic writing skills)
- Desirable: Experience with deep learning toolkits as well as good communication and presentation skills
Please submit all relevant documents (incl. curriculum vitae, certificates, motivation letter).
The final PhD topic is subject to your university.
Duration: 3 years
Need support during your application?
Kevin Heiner (Human Resources)
+49 711 811 12223
Need further information about the job?
Prateek Katiyar (Functional Department)
+49 711 811 91306