About this position
This project is a collaboration between Integreat amd the Bosch Centre for Artificial Intelligence (Germany).
The selected applicant will be employed at Bosch Centre for Artificial Intelligence (Germany) and will be enrolled in the PhD programme of the Faculty of Mathematics and Natural Sciences at the University of Oslo, and must adhere to all requirements of this PhD programme. It is a requirement to spend minimum 18 months during your PhD at University of Oslo, the actual time for your stays will be agreed upon individually.
The applicants will be evaluated by all partners. As part of the recruitment and evaluation process, shortlisted candidates will be invited to visit Bosch before possible employment.
Description
One of the most exciting frameworks to quantify uncertainty of predictions is conformal prediction (CP). Under appropriate exchangeability conditions, it provides a confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project will develop new CP methods for knowledge graphs (KGs), which are one of the most popular approaches for (semi-)structured data. There are many learning tasks that are based on KGs, such as KG completion, link prediction, and node and graph classification. Graph Neural Networks (GNNs) are very successful for learning on KGs and solving the mentioned tasks, but also have great potential for incorporating symbolic knowledge due to strong connections between GNNs and logics. We will develop methods for logic-aware CP on KGs using GNN for prediction and design new algorithms with theoretical guarantees. Then we will verify practical applicability and usefulness of these ideas and algorithms on benchmarks and on challenging real-world settings at BOSCH, with the possibility to develop industrial standard. This PhD project will be at the interface between statistics, logic and machine learning.
Requirements
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Master’s degree in statistics, logic, mathematics, theoretical computer science or a related quantitative subject with proven competence in statistics and/or logic and/or machine learning.
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Genuine interest in methodological research.
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Documented experience in scientific programming is necessary
Bosch offers:
- Competitive salary
- Access to travel budget for attending national and international conferences, schools, workshops, etc
- A unique research environment at Integreat and at Bosch with multiple opportunities to develop research themes at the forefront of modern science.
- A friendly professional and stimulating international working environment at Integreat and at Bosch.
- Access to a network of top-level national and international collaborators at Integreat and at Bosch.
- A vibrant international academic environment at Integreat and at Bosch.
- Career development programmes at Bosch and UiO and individual professional plan for the full duration of the doctoral research period.
- Funds through Integreat for shorter research mobility.
- Oslo’s and Stuttgart's family-friendly surroundings with their rich opportunities for culture and outdoor activities.
Supervisors
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Professor Arnoldo Frigessi, UiO, frigessi@uio.no contact person for inquiries about the position
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Associate Professor Evgeny Kharlamov, UiO and Bosch