Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- SciLifeLab
- Technical University of Denmark
- Chalmers University of Technology
- Delft University of Technology
- Ghent University
- Karolinska Institutet
- Stockholm University
- Aix-Marseille Université
- Delft University of Technology (TU Delft)
- NTNU Norwegian University of Science and Technology
- Eindhoven University of Technology (TU/e)
- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
- Department of Physics and Astronomy, Bologna University
- Eindhoven University of Technology
- Ludwig-Maximilians-Universität München •
- NTNU - Norwegian University of Science and Technology
- University of Oslo
- University of Twente (UT)
- Wageningen University & Research
- ; Max Planck Institute for Human Cognitive and Brain Sciences
- ; Technical University of Denmark
- ; University of Bristol
- ; University of Oxford
- ; Xi'an Jiaotong - Liverpool University
- AMOLF
- Aarhus University
- Constructor University Bremen gGmbH
- ETH Zurich
- IMEC
- Iowa State University
- Johannes Gutenberg University Mainz
- KTH Royal Institute of Technology
- Linköping University
- Max Planck Institute for the Study of Societies •
- Monash University
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Umeå University
- Umeå universitet
- University of Amsterdam
- University of Copenhagen
- University of Iceland
- University of Lethbridge
- University of Luxembourg
- University of Potsdam •
- Uppsala University
- Uppsala universitet
- Utrecht University
- VIB
- Wageningen University and Research Center
- 40 more »
- « less
-
Field
-
Dynamics (AIMD), and Machine Learning (ML) tools to develop theoretical electrocatalytic frameworks. Hereby, the project will challenge existing research on catalysis, move the boundary of fundamental
-
, develop methods to speed up this development by focusing on machine learning techniques to address sustainability challenges in chemistry research. We will explore novel pathways to process design and
-
central goal of the project is to develop explainable machine learning models that allow insight into the interaction between genetics and other types of data that can be used for developing tailored
-
: Conducting research on perception and situation understanding, making contributions to the state-of-the-art in the fields of simultaneous localization and mapping (SLAM), computer vision, machine learning
-
Job related to staff position within a Research Infrastructure? No Offer Description Epidemic processes widely apply to biological and computer network viruses, to cascading failures in power grids
-
assessments. The exceptional availability of Danish Big Dataset on health outcomes, consumption and sustainability. A unique combination of mass balance-based Source-to-Impact Models and Machine Learning
-
of the doctoral student The PhD project will aim at integrating single cell clonal, spatial and dissociated cell transcriptomics data for 3D neurodevelopmental reconstruction using a machine learning approach and
-
these CSRS spectra by machine learning algorithms. Your mission is to set up and characterize backscattering CSRS microscopes and evaluate their functionality on cancer tissue. Your tasks will include
-
. Novel spectrometer concepts, multi-focus and wide-field illumination approaches will be put in place. Precise diagnoses of cancerous tissues will be derived from these CSRS spectra by machine learning
-
collectively offer expertise in computational biology, genetics, epidemiology, and machine learning. The research will be closely linked to the WISDOM project, an EU-funded initiative coordinated by the main