Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Sveriges Lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Manchester Metropolitan University;
- University of Groningen
- CNRS
- Delft University of Technology (TU Delft); Published today
- Faculty of Science, Charles University
- Instituto de Ciencias del Patrimonio - Spanish Council for Scientific Research (CSIC)
- KU Leuven
- Loughborough University
- University Medical Center Utrecht (UMC Utrecht)
- University of Birmingham
- University of Exeter;
- Utrecht University
- Vrije Universiteit Brussel
- Aalborg University
- Aarhus University
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Cranfield University
- Delft University of Technology (TU Delft)
- ETH Zürich
- Edinburgh Napier University;
- FCiências.ID
- Fraunhofer-Gesellschaft
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- Instituto Superior Técnico
- Instituto Superior de Agronomia
- Leibniz
- Loughborough University;
- MASARYK UNIVERSITY
- Masaryk University - Faculty of Arts
- Nature Careers
- New York University
- Technical University of Munich
- Temple University
- UNIVERSIDAD POLITECNICA DE MADRID
- UNIVERSITE LE HAVRE NORMANDIE
- Universidade de Trás-os-Montes e Alto Douro
- Universitat Rovira i Virgili
- University of Basel
- University of Birmingham;
- University of Copenhagen
- University of East Anglia;
- University of Exeter
- University of Göttingen •
- University of Münster •
- University of Plymouth
- University of Plymouth;
- Università degli Studi di Brescia
- Université Catholique de Louvain (UCL)
- Uniwersytet Warszawski
- Wageningen University & Research
- 42 more »
- « less
-
Field
-
using an individual-based framework in R and NetLogo with GIS integration. Individuals will make state- and context-dependent decisions, trading off energy gain, moisture balance, shelter, exposure
-
, processing video data, and applying AI models to improve efficiency in population and behavioral analyses. Fieldwork will be combined with statistical and spatial analysis using RStudio and GIS tools. In
-
may include site visits and data collection. Experience in numerical modelling, GIS, or hydrodynamics is desirable, but not essential and training will be provided. Prior research experience and
-
start date: October 2026. Please quote the reference: SciEng-AY-2026-27-GI Cancer Cachexia
-
all-embracing way the development of its spatial differentiation, as well as interactions between social (socioeconomic and sociocultural systems) and natural environment, also via applying GIS
-
, epidemiological, and environmental data Taking part in developing and validating predictive cancer‑risk models Contributing to spatial analysis and data integration in geographic information systems (GIS
-
hazards and assessing their risk for the society. At the same time, they are fully qualified users of remote sensing, GIS and statistictical software techniques that can be applied to geoscience and
-
spreads in natural waters. Training will cover microbial genomics, evolution assays, GIS, and advanced statistics, alongside transferable skills in interdisciplinary collaboration and science communication
-
for GIS, cartographic maps, geodata infrastructures and geo-analytical workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g
-
or habitats knowledge of data analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity