Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- France
- Germany
- Sweden
- Portugal
- Denmark
- Belgium
- Switzerland
- Spain
- Czech
- Canada
- Austria
- Finland
- Norway
- Australia
- Italy
- Ireland
- Romania
- Singapore
- United Arab Emirates
- Morocco
- Poland
- Estonia
- Hong Kong
- Japan
- Taiwan
- Brazil
- China
- Croatia
- Cyprus
- Europe
- Greece
- Lithuania
- Luxembourg
- Macau
- 27 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Economics
- Earth Sciences
- Engineering
- Science
- Mathematics
- Environment
- Materials Science
- Humanities
- Social Sciences
- Arts and Literature
- Chemistry
- Business
- Linguistics
- Electrical Engineering
- Psychology
- Design
- Education
- Physics
- Sports and Recreation
- 12 more »
- « less
-
-seq, ATAC-seq, spatial transcriptomics, …) into modeling and develop efficient data/training pipelines Drive application cases with Helmholtz Munich, MDC Berlin, and NVIDIA—for example, disease modeling
-
University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 1 month ago
areas that advance geospatial concepts and theory, including: spatiotemporal modeling, Natural Language Processing implemented within the spatial domain, Big Data cloud computing for spatial statistical
-
Deutsches Zentrum für Neurodegenerative Erkrankungen | Ulm, Baden W rttemberg | Germany | about 2 months ago
sclerosis (ALS) and Parkinson’s disease. Using next-generation sequencing, we have identified Mendelian disease genes that cause autosomal-dominantly inherited ALS. We have developed innovative disease models
-
. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
-
the tissue response around the materials will be followed by multimodal approaches including (among others) time-lapsed in vivo imaging, multiphoton intravital microscopy, spatial transcriptomics and
-
scRNASeq and spatial transcriptomics datasets, including probing gene signature expression and comparing expression between groups using correct statistical models (e.g., Linear Mixed Model, Bayesian
-
neurodevelopmental and neuropsychiatric disorders using mouse as a model organism. The primary function of this position includes functional characterization of genetically modified mice carrying disease-related
-
-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
-
of priority elasmobranch species in the study area, while managing and analysing large telemetry datasets, and integrating environmental/spatial data to address key research questions on species ecology and
-
applied questions such as environmental management and risk assessment. For more information on EnvStat, please see https://www.helsinki.fi/en/researchgroups/environmental-and-ecological-statistics TWO