Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Forschungszentrum Jülich
- CNRS
- Aalborg University
- Norwegian University of Life Sciences (NMBU)
- Duke University
- University of Nottingham
- University of Texas at El Paso
- Cranfield University
- DAAD
- George Mason University
- Leibniz
- Medical University of Innsbruck
- Newcastle University
- Technical University of Denmark
- Technical University of Munich
- University of Bergen
- University of Twente (UT)
- Western Norway University of Applied Sciences
- ;
- AALTO UNIVERSITY
- Aarhus University
- Amsterdam UMC
- Centrale Supelec
- Centre Euopéen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS)
- Cornell University
- Delft University of Technology (TU Delft)
- Ecole Centrale de Lyon
- Erasmus MC (University Medical Center Rotterdam)
- IMEC
- Indra Deimos
- London School of Economics and Political Science;
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Intelligent Systems, Tübingen, Tübingen
- Maynooth University
- Nicolaus Copernicus Astronomical Center
- Northeastern University London
- Oak Ridge National Laboratory
- SciLifeLab
- Technische Universität Ilmenau (Germany)
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- UNIVERSITY OF VIENNA
- UTTOP
- University of Amsterdam (UvA)
- University of Exeter
- University of Newcastle
- University of North Texas at Dallas
- University of Oslo
- University of Sheffield
- University of Stuttgart
- University of Texas Rio Grande Valley
- University of Vienna
- Universität Wien
- VUB Vrije Universiteit Brussel
- 45 more »
- « less
-
Field
-
statistical tools (R and/or Python). Develop and conduct optimisation modelling (e.g. electricity market and grid dispatch). Assist in literature reviews and summarising academic research. Contribute to writing
-
and applying high-resolution time-lapse GPR and EMI imaging methods at multiple scales to enhance our understanding of subsurface flow Designing and implementing novel inversion algorithms for GPR and
-
diagnosis is often challenging for patients presenting with vague, non-specific symptoms that may be linked to multiple cancer sites. This project aims to improve diagnostic decision-making in such patients
-
, including, but not restricted to, geometry or shape optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience
-
(eDNA) approaches for biodiversity assessment across multiple habitat types. The PhD project will focus on applying and developing eDNA‑based methods to assess biodiversity and ecological communities in
-
., PsychoPy, E-Prime, Gorilla, Presentation). Hands-on experience in data visualization, data analysis, and programming in R and/or Python. Experience in, and aptitude for, complex statistical modelling (inc
-
trigger redesigns across multiple groups. The challenge is compounded by the fact that each discipline uses different data models and representations, making system-level interdependencies difficult
-
Science, or a closely related field Prior coursework and working experience in data science, machine learning, statistics, or related areas Proficiency in Python for data analysis and modeling, machine learning
-
productivity. Multiple coordinated observing strategies, including research vessels and a large ensemble of autonomous platforms, will collect physical, chemical, and biological datasets across scales
-
related fire regimes by conducting factorial experiments using multiple climate-change scenarios Requirements: a master’s degree in biophysical, environmental and/or ecological sciences ability to work with