Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Chalmers University of Technology
- Swedish University of Agricultural Sciences
- Umeå University
- University of Lund
- SciLifeLab
- Linköping University
- Lulea University of Technology
- Mälardalen University
- Jönköping University
- Karlstad University
- Linnaeus University
- Örebro University
- 3 more »
- « less
-
Field
-
position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
-
description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
-
learning. The employment is full-time for two years starting from August 1st 2025 or by agreement. Apply latest April 7th 2025. Project description Geometric deep learning refers to the study of machine
-
physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
-
postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
-
computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
-
of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department
-
the postdoctoral appointment’s nature as a career-development position for junior researchers, we are looking for candidates who have completed their PhD no more than three years before the application deadline
-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
-
on machine learning solutions and data visualisation. In addition will some cod individuals be tagged, and their behaviour be monitored using acoustic telemetry. The cod behaviour could also be correlated with