Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- France
- Germany
- Sweden
- Portugal
- Denmark
- Belgium
- Switzerland
- Spain
- Canada
- Czech
- Austria
- Finland
- Norway
- Australia
- Italy
- Ireland
- Romania
- Singapore
- United Arab Emirates
- Morocco
- Poland
- Estonia
- Japan
- Hong Kong
- Taiwan
- Brazil
- China
- Croatia
- Cyprus
- Europe
- Greece
- Lithuania
- Luxembourg
- Macau
- 27 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Economics
- Engineering
- Earth Sciences
- 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
-
, marking a bold step toward a more collaborative, challenge-driven model of research. Team Science Scientific breakthroughs rarely come from isolation—they emerge when brilliant minds connect. Our Team
-
networks driving aging and inflammation using cutting-edge molecular and genomic technologies. The project integrates single-cell and spatial transcriptomics, epigenome and whole-genome sequencing, and
-
biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
-
of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods
-
information across scales. In this project, you will leverage the large soil database (>2000 profiles) hosted by the Soil Functions and Dynamics group, along with soil spatial modeling techniques, to assess
-
new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
-
spatial and non-spatial data efficiently. Develop and implement ETL processes to prepare data for publication, analysis, and visualisation, including metadata and data packaging. Collaborate in an agile
-
expertise, including facilities for high-throughput screening and high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners
-
-dimensional cytometry data. The successful candidate will play a key role in processing, analyzing, and modeling complex biomedical data - integrating spatial imaging, CyTOF, and clinical data - to enable
-
Professor who wants to contribute to advance science, teaching and practice at the interface of Biodiversity, Land Use and Spatial Planning. By planning and governance of land use it is possible to halt