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Machine Learning

Research group We do research in machine learning, with both method and theory development in and applications with e.g. cancer research and life science.

Machine learning (ML) is a subarea within artificial intelligence (AI) where the focus is to learn from data. Machine learning uses collected data, for instance an image and knowledge about something we're looking for in the images, to automatically find the settings for a mathematical model of the connection between for instance an image and what's sought in the image. With the mathematical model, we can then predict whether what we're looking for is in a new image or not.

We currently have two open positions:

We currently have a PhD position in machine learning open in the group. The project is about developing structured priors and penalties for analysing image data. See the full ad and apply here:

We are currently hiring a post-doctoral researcher to develop the next generation variational autoencoders for analysing gene isoforms in single-cell data. This is a collaboration with Johan Henriksson at MIMS (www.henlab.org). See the full ads and apply here:

 

Head of research

Tommy Löfstedt
Associate professor
E-mail
Email

Overview

Participating departments and units at Umeå University

Department of Computing Science, Faculty of Science and Technology

Research area

Cancer, Computing science

External funding

The Kempe Foundation, Swedish Research Council

External funding

Three million SEK to AI project to improve the treatment of child cancer

Funded by the Childhood Cancer Fund, Tommy Löfstedt will automate radiation therapy in pediatric oncology.