Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- DAAD
- Leibniz
- Technical University of Munich
- Humboldt-Stiftung Foundation
- Nature Careers
- University of Göttingen •
- University of Potsdam •
- Hannover Medical School •
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Plant Breeding Research •
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute of Molecular Plant Physiology •
- University of Cologne •
- University of Stuttgart •
- University of Tübingen
- 8 more »
- « less
-
Field
-
Description The majority of hydrological models rely heavily on the principle of mass balance, often represented through Ordinary Differential Equations (ODEs). These models encapsulate
-
Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
-
Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
-
teacher-student synchronization. However, this synchronization necessitates an exact student model, making the ACT often inexact and susceptible to uncertainty and variability. The project will aim
-
Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
-
significantly slows down the development of new desirable nanostructures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA
-
the change! We offer ideal conditions for you to complete your doctoral degree: Competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling
-
The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
-
the goal to mechanistically explore the interaction of phytonutrients in the plant-environment response in order to enhance and secure the nutritional quality of vegetables under changing climatic conditions
-
conditions and under the impact of the food supply chain, including food processing. In this context, the aim of the PhD project is to investigate the influence of drought stress on sulphur-containing plant