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or Functional ultrasound imaging or Electrophysiology (neuropixels) in behaving animals Quantitative data analysis and computational modeling of network activity Data acquisition systems, signal processing and
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Postdoc in experimental studies of phase behavior of ABC-miktoarm star block copolymers in thin f...
on working in Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your complete online application must be submitted no later than 1 June 2026 (23:59 Danish time). Apply at: Postdoc in
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models, for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics), large textual corpora (e.g., scientific literature), and/or pathologic images. Our research
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-, outcome- and sensory-guided actions, and how these processes are disrupted in genetic neurodevelopmental disorder models, including autism, OCD, ADHD, and intellectual disability. Postdocs will work in a
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Aarhus University (http://bio.au.dk/en) and work in the Archaea Group (https://bio.au.dk/en/research/research-areas/microbial-processes-and-diversity/archaea-group), Section for Microbiology
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and skill in programming with MATLAB or Python. Research experience in MEG, in vivo electrophysiology, in vivo two-photon/miniscope imaging, slice electrophysiology, and mouse brain surgery is desired
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, and deep generative models (e.g., VAEs, normalizing flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO
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Chemical Biological Centre (https://www.umu.se/en/kbc ) at Umeå University and is affiliated with the national Centre of Excellence – Umeå Centre for Microbial Research (UCMR) (https://www.umu.se/en/ucmr
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studies fundamental processes in endothelial cells driving cardiometabolic diseases including atherosclerosis, thrombosis and type 2 diabetes. In particular, the team interrogates the role of endothelial
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural