26 biosignal-processing-machine-learning Postdoctoral positions at Utrecht University
Sort by
Refine Your Search
-
Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
-
their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
-
against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
-
; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
-
done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized on location (Western Scheldt and
-
for reasoning, on efficient and explainable machine learning for extracting and structuring information from large datasets, and on combining the two in neuro-symbolic AI.
-
Sciences of Utrecht University. UIPS focuses on processes around discovery, development, and use of drugs and medical nutrition using molecular and technological principles from the Natural and Life Sciences
-
sediment management. This will be done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized
-
and authorities interested in improving civic participation. The research in this postdoctoral position focuses on text and image feature learning for news ecosystems, analysing the complex
-
Sciences of Utrecht University. UIPS focuses on processes around discovery, development, and use of drugs and medical nutrition using molecular and technological principles from the Natural and Life