Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Technical University of Denmark
- University of Twente
- Nature Careers
- Rutgers University
- Pennsylvania State University
- European Space Agency
- Heriot Watt University
- KINGS COLLEGE LONDON
- Technical University of Munich
- University of London
- University of Southern Denmark
- ;
- ; University of Southern Denmark
- Aarhus University
- Argonne
- Brookhaven Lab
- Cornell University
- King Abdullah University of Science and Technology
- King's College London
- McGill University
- Michigan Technological University
- San Diego State University
- UNIVERSITY OF HELSINKI
- University of Basel
- University of Birmingham
- University of Miami
- University of Minnesota
- University of North Carolina at Chapel Hill
- University of Nottingham
- University of Oslo
- University of Utah
- Wayne State University
- Western Norway University of Applied Sciences
- 23 more »
- « less
-
Field
-
for companies to develop new and innovative services and products which benefit people and create value for society. DTU Health Techs expertise spans from imaging and biosensor techniques, across digital health
-
biomarkers, clinical, and cognitive variables, genotyping and sequencing data, and MRI brain imaging data on patients with severe mental disorders. In addition, we work closely with national population cohorts
-
languages such as Python, MATLAB, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) preferred. Familiarity with medical imaging processing and reconstruction techniques
-
point cloud data processing, deep learning for time series data prediction, digital twin, geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems, crowd simulation
-
asset. Familiarity with quantitative text analysis procedures is considered an advantage. Familiarity with digital tools, including computational methods for textual analysis, will be an advantage
-
. For modeling, we use both public and proprietary clinical and research data and generate our own repository of digital pathology images. A further focus of our lab is the improvement of digital pathology
-
optimization. Basic knowledge of integrated circuit design, including digital simulation and logic synthesis. methods, and other related topics pertaining to fast AI model inference. Experience working in
-
). The successful applicant will initially be involved with DOD-funded clinical projects focused on assessment of bone quality using new methods based on digital tomosynthesis imaging, and identifying strategies