Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- CNRS
- Forschungszentrum Jülich
- Norwegian University of Life Sciences (NMBU)
- Aalborg University
- University of Bergen
- University of Nottingham
- University of Texas at El Paso
- Cranfield University
- Duke University
- George Mason University
- Medical University of Innsbruck
- Newcastle University
- SciLifeLab
- Technical University of Denmark
- Technical University of Munich
- University of Twente (UT)
- Western Norway University of Applied Sciences
- ;
- Aarhus University
- Centrale Supelec
- Cornell University
- DAAD
- Delft University of Technology (TU Delft)
- Dublin City University
- ETH Zürich
- Ecole Centrale de Lyon
- Erasmus MC (University Medical Center Rotterdam)
- IMEC
- Inria, the French national research institute for the digital sciences
- Leibniz
- 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
- Nicolaus Copernicus Astronomical Center
- Northeastern University London
- Oak Ridge National Laboratory
- Sorbonne University, IMPMC-UMR 7590
- Swedish University of Agricultural Sciences
- Tampere University
- Technical University Of Denmark
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- UNIVERSITY OF VIENNA
- UTTOP
- University of Cambridge
- University of Exeter
- University of Lincoln
- University of Newcastle
- University of North Texas at Dallas
- University of Oslo
- University of Plymouth
- University of Sheffield
- University of Southampton
- University of Texas Rio Grande Valley
- University of Vienna
- Universität Wien
- Université de Caen Normandie
- Uppsala universitet
- VUB Vrije Universiteit Brussel
- 50 more »
- « less
-
Field
-
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
-
, machine learning, deep learning, high powered computing (requiring Python etc) or a combination of data science and qualitative methods (e.g., interviews and focus groups). Project themes include (but
-
chemical exchange saturation transfer. By combining multiple modalities and parameters, we aim to identify at risk sites for GBM relapse at the earliest opportunity, before progression becomes apparent
-
., 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
-
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
-
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
-
concentrates on global design of the turbomachinery stages for decarbonization. PhD Objectives The overarching objective of the PhD thesis research project is to combine numerical tools with multiple levels
-
modeling framework will be designed to support multiple downstream applications, including energy flexibility assessment, advanced control strategies (e.g., MPC and RL), and evaluation of renovation and
-
PhD students (multiple positions) Artificial Intelligence within Public Health Research (all genders) Start date: 01.10.2026 Contract type: 3 years (fixed-term) Location: Wildau Deadline: 30.04.2026
-
, extremes, and concept shift Explore equation discovery and dependency-testing ideas to obtain deterministic, interpretable representations of plant carbon allocation and plant water status Integrate multiple