Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
We have an exciting position for a curious post-doctoral researcher with expertise in community dynamics modelling, to contribute to our research on the effects of climate warming on aquatic food
-
will join a multidisciplinary research program that combines experimental models, patient-derived materials, and advanced technologies to explore the mechanisms that preserve auditory system homeostasis
-
northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
-
tomorrow. About the department The main competences at the Department of Industrial and Materials Science are found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation
-
, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
-
diseases, including genetics, epidemiology, immunology and epigenetics, with excellent clinical cohorts and experimental models. The Applied Immunology & Immunotherapy group is physically located
-
proteins implicated in diseases associated with their aggregation and fibril formation. These systems are characterized using both purified and complex samples. The work is focussed on the development of a
-
well as other initiatives around repairability, is unclear. The postdoc will explore impacts and challenges for different actors involved, including ensuring a steady supply of spare parts, the complexities
-
to emerging digital technologies Interplay between technology development and business model evolution - how advancements in technologies reshape value creation and value capture, necessitating continous
-
This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The