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Bosch Industry-on-Campus Lab, University of Tübingen and Bosch Center for AI (BCAI)
Application deadline : 31.05.2021
The Bosch Industry-on-Campus Lab, a research collaboration between the University of Tübingen and Bosch Center for AI (BCAI), invites applications for an open
PhD position (m/f/d; E13 TV-L, 80%)
in Compositional Data Synthesis. The aim of this project is to learn how to synthesize new, previously unseen visual scenes through object compositionality. A bias to account for the compositional way in which humans structure a visual scene in terms of objects has frequently been overlooked. In this project, you will investigate object compositionality as an inductive bias for deep generative models, such as generative adversarial networks (GANs). Specifically, you will focus on how to generate novel unseen compositions of objects present in the training set.
You will be jointly supervised by Prof. Dr. Zeynep Akata from the University of Tübingen side and Dr. Anna Khoreva from the Bosch side.
The position is available immediately (but start date is negotiable), the contract is initially for three years, and remunerated according to the German salary scale 13 TVL.
What are you going to do?
As part of the Bosch Industry-on-Campus Lab at the University of Tübingen, you are going to carry out AI research and develop novel deep generative models, learning to synthesize new data samples through the notion of compositionality. There will also be regular visits and interactions with researchers at Bosch Center for AI, who have an office on campus. At the University of Tübingen you will be supervised by Prof. Dr. Zeynep Akata and Dr. Anna Khoreva.
Your tasks will be to:
- Develop new computer vision and/or deep machine learning methods on compositional data synthesis;
- Collaborate with other researchers within the lab and BCAI Research;
- Complete and defend a PhD thesis within the official appointment duration of three years;
- Regularly present internally on your progress and help Bosch write patent applications to protect inventions from the lab when requested.
- Regularly present intermediate research results at international conferences and workshops, and publish them in proceedings and journals;
- Potentially assist in relevant teaching activities.
What do we require?
- Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or related field;
- Strong background in computer vision and/or machine learning;
- Excellent programming skills, preferably in Python;
- Prior experience of working with deep learning libraries, such as PyTorch or TensorFlow;
- Solid mathematics foundations, especially in probability theory, statistics, calculus and linear algebra;
- High motivation and creativity;
- Strong communication, presentation and writing skills and excellent command of English.
Prior publications in relevant vision and machine learning venues as well as experience working with deep generative models (e.g. VAEs, GANs, Flows) will be advantageous for your application.
Application
The University of Tübingen is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We seek to increase diversity and the number of women in areas where they are under-represented and therefore explicitly encourage women to apply. We are also committed to recruiting more people living with disabilities and strongly encourage them to apply. The employment will be carried out by the central administration of the University of Tübingen.
Do you recognize yourself in the job profile? Then we look forward to receiving your application by May 31st, 2021. Please note the position will be filled as soon as an appropriate candidate is found.
Your application should consist of a single PDF file <lastname_firstname>.pdf containing:
- A two-page motivational letter, which: 1) explains why you would like to join us and 2) describes the research topics that excite you and that you would like to pursue in your PhD;
- Your CV, with details of publications and conference participations (if applicable);
- A copy of your Master’s degree certificate, if you already have one;
- Unofficial transcripts of all of your university studies (BSc and MSc), as well as a translation into English and explanation of grading system (if needed);
- Letters of recommendation and/or contact details of 2-3 referees;
- Link to github or enclosed code sample you have written;
- Optionally, additional documents such as a thesis, published papers, or project portfolios.
You may apply by sending your documents to eml-sekretariat@inf.uni-tuebingen.de.
