Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Gothenburg
- University of Vienna
- UNIVERSITY OF VIENNA
- Texas A&M University
- Northeastern University
- Rutgers University
- Stanford University
- Texas A&M University System
- University of Copenhagen
- Francis Crick Institute
- Georgetown University
- Helmholtz Association of German Research Centres
- UNIVERSITY OF HELSINKI
- University of Helsinki
- Vrije Universiteit Amsterdam
- Yale University
- Aarhus University
- Arizona State University
- Carnegie Mellon University
- Chalmers University of Technology
- Cleveland Clinic
- European Magnetism Association EMA
- Flinders University
- Indiana University
- Max-Planck-Institut für Mikrostrukturphysik
- Michigan State University
- NEW YORK UNIVERSITY ABU DHABI
- New England HERC
- Pennsylvania State University
- Roskilde University
- Shenzhen University of Advanced Technology
- University of British Columbia
- University of Florida
- University of Kansas Medical Center
- University of Maryland, Baltimore
- University of Texas at Austin
- University of Tokyo
- University of Utah
- University of Washington
- Vanderbilt University
- Whitehead Institute for Biomedical Research
- 31 more »
- « less
-
Field
-
modelling, hybrid modelling and/or machine learning to study ecosystem processes, as well as with handling of big data and/or processing of Earth observation data. Specifically, experience with Python
-
approaches. Beyond this research focus, the Division has a strong complementary background on using local scale community data such as vegetation plot data (e.g. EVA, https://euroveg.org/eva-database and
-
in statistical machine learning, analysis of high-dimensional networks, and integrative analysis of complex biological data, including big omics data. Dr. Floyd is Co-Director of the UW Cardiovascular
-
(DL), and big data analytics. His lab is developing new modeling strategies that can integrate heterogeneous public data into model development. Another major research interest is the use of large
-
biomarkers for brain diseases, particularly Alzheimer's disease. A large amount of data on fluid biomarkers has been generated in multiple international collaborative projects, and we are now
-
or lead “big data” analyses to identify areas with low testing coverage and inform placement/targeting of community-based HIV testing. • Integrate, clean and harmonize multiple data sources (e.g
-
encompasses both clinical and experimental studies as well as data analysis of clinical and epidemiological data. Subject area Psychopharmacology Subject area description Psychopharmacology
-
, animal models of infection, and microscopy. Multi-omics approaches and big data analysis will be included. Perform data analysis, prepare data for presentations (oral and written), write manuscripts and
-
. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
-
. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed