Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- INESC TEC
- Nanyang Technological University
- City of Hope
- King Abdullah University of Science and Technology
- LINGNAN UNIVERSITY
- NTNU Norwegian University of Science and Technology
- UCL;
- Universidade do Minho
- University of Bergen
- University of British Columbia
- University of Colorado
- Dalhousie University
- ETH Zürich
- Harvard University
- Indiana University
- Johns Hopkins University
- Northeastern University
- SUNY University at Buffalo
- Simons Foundation/Flatiron Institute
- Technical University of Munich
- UNIVERSITY OF SYDNEY
- Universidade de Coimbra
- University of Nottingham
- University of Nottingham;
- University of Oslo
- University of Sydney
- University of Texas Rio Grande Valley
- University of Texas at Austin
- University of Turku
- Western Norway University of Applied Sciences
- Yale University
- Zintellect
- 23 more »
- « less
-
Field
-
techniques. You will have the opportunity to participate in various projects utilizing artificial intelligence (AI) and machine learning (ML) to develop applications that optimize combat casualty care
-
-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
-
, statistical analysis, and machine learning-enabled decision-making • Prototype, integrate, and optimise suitable open-source hardware and software solutions for automated experimentation, including laboratory
-
Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
& Medicine. This is an exceptional opportunity for a talented and ambitious researcher to build an independent, high-impact research program at the intersection of machine learning and healthcare
-
, with applications ranging from scientific research to medical imaging and marketing analysis. With the ever increasing amount of learning data, these algorithms face computational challenges
-
scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
-
of novel computational/biostatistical/machine learning methods for the integration of multiple, diverse dataset and the synthesis of hypotheses around the molecular mechanisms that drive the co-occurring
-
Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics Duties will include, but are not
-
in the health sciences, including fields such as healthcare informatics, movement and rehabilitation sciences, medical imaging, remote sensing, computer vision, mental health, data fusion
-
, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists Strong oral and written communication, data