Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- United Kingdom
- Germany
- Sweden
- Netherlands
- Belgium
- Portugal
- Norway
- Switzerland
- Czech
- Denmark
- Spain
- Canada
- Finland
- Australia
- Austria
- Estonia
- Singapore
- Poland
- Hong Kong
- United Arab Emirates
- Italy
- Ireland
- Japan
- Luxembourg
- Morocco
- Romania
- Brazil
- India
- Lithuania
- Slovakia
- Slovenia
- Taiwan
- 24 more »
- « less
-
Program
-
Field
-
. 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
-
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
-
Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | about 2 months ago
administrative housing data, environmental indicators, and accessibility metrics — and apply advanced spatial methods such as multilevel modelling and geographically weighted regression to identify relevant
-
the fundamental factors governing cation mobility in aluminosilicate materials through an integrated experimental-theoretical-computational approach. The research will probe the spatial extent and timescales of ion
-
. 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
-
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
-
materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
-
interdisciplinary research group dedicated to developing integrated approaches to geospatial systems analysis. Our team pushes the boundaries of how spatial data can be used to tackle today’s pressing environmental
-
are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
-
decision-support systems for sustainable forest-based supply chains in close collaboration with industrial partners. These projects aim to develop interactive methods, computational models, artificial