7 machine-learning-phd scholarships at Umeå universitet in Sweden

PhD student in Computing Science with focus on machine learning for continuous and discrete structures

graph based machine learning for discrete and continuous structures, led by Frank Drewes, Johanna Björklund, and Henrik Björklund. The PhD student will work within the context of the STING (Synthesis and

PhD position in mathematics or mathematical statistics, with focus on geometric deep learning

26th 2024. Project description and tasks Machine learning (‘artificial intelligence’) is having an immense impact on both society at large and research especially, and this impact is expected to increase

PhD position in Computational Sciences within the national Data-Driven Life Sciences program

problem or what heuristics organisms might evolve. This research project is a collaboration between Eric Libby and Laura Carroll. It involves using machine learning techniques to infer the mechanisms by

PhD position in Mathematics focusing on geometric deep learning

of topics in modern machine learning research, including geometric deep learning, non-convex optimization problems and federated learning. In addition, this project is deeply connected with

1 to 2 PhD student/s in Computing Science with focus on Interactive Systems that Reason Spatially

etc.) Automated reasoning Machine learning Candidates are expected to have good knowledge in Artificial Intelligence and good programming skills in some of the following: Python, PyTorch library, OpenAI

PhD student in Computing Science with focus on Cybersecurity

will be predominantly conducted in English. Experience in broad areas of expertise, including machine learning algorithm development, statistical methods, distributed learning, and cybersecurity, is

PhD Student in Medical Science

the development of new techniques for rehabilitation and functional impairments of injuries to the upper extremity supported by machine learning and neural networks. The position is an initiative within