23 machine-learning-phd Fellowship positions at UiT The Arctic University of Norway

PhD Fellow in knowledge-driven machine learning

Stig Brøndbo 15th May 2024 Languages English English English Faculty of Science and Technology PhD Fellow in knowledge-driven machine learning Apply for this job See advertisement The position Join

PhD Fellow in knowledge-driven machine learning

-driven machine learning, is seeking to recruit a fulltime PhD student at the UiT The Arctic University of Norway for a cross-disciplinary project across machine learning, statistics and logic, which is

PhD Fellow in Machine Learning for graphs and time series data

Description The position A PhD position in machine learning for graphs and time series data is available at the Department of Mathematics and Statistics , Faculty of Science and Technology . The position is

PhD Fellow in Machine Learning for graphs and time series data

Stig Brøndbo 2nd May 2024 Languages English English English Faculty of Science and Technology PhD Fellow in Machine Learning for graphs and time series data Apply for this job See advertisement

PhD Fellow in the intersection of information theory and deep learning

Torbein Kvil Gamst 28th May 2024 Languages English English English Faculty of Science and Technology PhD Fellow in the intersection of information theory and deep learning Apply for this job See

PhD Fellow in Computer Science

machine learning and with strong programming skills, and with an interest in working in close collaboration with industry. Working environment: The project will be done in an interdisciplinary team

PhD Fellow in Translational Cancer Research

Associate Professor Mehrdad Rakaee. Key responsibilities of the candidate: Developing innovative approaches: You will be responsible for developing machine learning and algorithms to manage and analyze next

PhD Fellow in Computational Geometry and Simulations

for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD

PhD Fellow in Computational Geometry and Simulations

for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD

PhD Fellow in Deep Learning and statistics for heterogeneous data

Stig Brøndbo 30th April 2024 Languages English English English Faculty of Science and Technology PhD Fellow in Deep Learning and statistics for heterogeneous data Apply for this job See