Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- United Kingdom
- Germany
- Sweden
- Netherlands
- Portugal
- Belgium
- Norway
- Czech
- Switzerland
- Denmark
- Spain
- Canada
- Finland
- Australia
- Austria
- Estonia
- Singapore
- Poland
- United Arab Emirates
- Hong Kong
- Italy
- Ireland
- Japan
- Luxembourg
- Morocco
- Romania
- Brazil
- India
- Lithuania
- Slovakia
- Taiwan
- 23 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Economics
- Mathematics
- Science
- Engineering
- Earth Sciences
- Social Sciences
- Environment
- Arts and Literature
- Humanities
- Materials Science
- Business
- Education
- Linguistics
- Chemistry
- Design
- Electrical Engineering
- Sports and Recreation
- Law
- Physics
- Psychology
- 13 more »
- « less
-
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
-
. 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
-
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
-
NIMSB Technology Platform Leaders:Data Science, Single-Cell & Spatial Omics, Proteomics/Metabolomics
Single-cell and Spatial Omics: https://nimsb.unl.pt/wp-content/uploads/2026/03/SComicsTPL-1.pdf Proteomics/Metabolomics:https://nimsb.unl.pt/wp-content/uploads/2026/03/ProteomicsTPL-1-1.pdf Skills We seek
-
deep learning models (e.g., adapting methods in [6]) based on spatial cellular graphs constructed from these images to predict clinical outcomes. The research will be carried out using two
-
, Digital Soil Mapping, Remote sensing (COPERNICUS data ecosystem), spatial data modelling, spatial analysis, neural networks, large scale datasets management with GIS, cloud computing, Big Data tools. You
-
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 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
-
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
-
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