Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- United Kingdom
- Germany
- Sweden
- Netherlands
- Portugal
- Belgium
- Norway
- Switzerland
- Czech
- Denmark
- Finland
- Canada
- Spain
- Austria
- Estonia
- Poland
- Australia
- Singapore
- Hong Kong
- Italy
- Morocco
- United Arab Emirates
- Ireland
- Japan
- Luxembourg
- Brazil
- Iceland
- India
- Lithuania
- Slovakia
- Slovenia
- 23 more »
- « less
-
Program
-
Field
-
NAME_FAMILY NAME) : https://nextcloud.univ-lille.fr/index.php/s/ezJxfSBwTjkJCnt Key words: solidification, recycled aluminum alloys, induction heating, thermal simulations, 3D modelling, mechanical testing
-
. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
-
(PDEs) and modelling with PDEs. The applicant’s research focus must be a specialisation in numerical analysis for PDEs. The specialisation should both strengthen the division’s current research in
-
nécessaire pour suivre les bilans des gaz à effet de serre, la production de biomasse et les rendements agricoles. À ce jour, la plupart des méthodes permettant d'estimer spatialement la GPP s'appuient soit
-
statistical models. Within the Polarity, Division and Morphogenesis team, the candidate will work closely with biologists and physicists to develop approaches integrating spatial transcriptomics, cell dynamics
-
the molecular signatures of proteostasis loss and identify early markers of proteostatic failure. The role combines wet-lab spatial biology with computational approaches. You will work across models and scales
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
that is focused on the study of human tumors through the use of multiple genomic technologies. The methods used include gene expression profiling using bulk RNAseq and scRNAseq, DNAseq, and spatial
-
for therapeutic intervention. This PhD project will leverage large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology to develop models, including transformer-/graph-based models
-
. The project will construct the first-ever Spatial Integrated Assessment Model of the global water cycle. Combined with global spatial data on economic activity, water usage, and atmospheric evaporation
-
LiDAR-based ecology. We're looking for candidates with strong technical skills and ecological interest—people who want to use LiDAR, AI, and spatial modeling to advance our understanding of vegetation