Sort by
Refine Your Search
-
Country
-
Employer
- ; University of Warwick
- ; University of Exeter
- ; University of Reading
- ; University of Sussex
- Institut Pasteur
- Ludwig-Maximilians-Universität München •
- NTNU - Norwegian University of Science and Technology
- Norwegian University of Life Sciences (NMBU)
- Technical University of Denmark
- University of Groningen
-
Field
-
will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
-
Muscle Dynamics: Approximate muscles as “cables” with Hill model dynamics within the SOFA framework. Simulate muscle contraction patterns and their interaction with the larva’s environment, including
-
infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good
-
sequences, analyse those data using Bayesian, Maximum Likelihood and coalescence approaches, and build matrices of geolocation and morphological data. The work will be alongside others working on related
-
. Integrate hydraulic-hydrologic modeling and surrogate models (e.g., Bayesian Networks) to simulate stormwater behavior under future scenarios. Apply optimization techniques to design and evaluate nature-based
-
research, in and outside academia. The focus for the PhD work will be probabilistic structural lifetime estimation of offshore dynamic riser and power cable systems by use of continuous measurements
-
expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
-
changes (so called swelling). Swollen batteries are at risk of rupturing which may significantly shorten their lifetime. Development of advanced computer models is critical for understanding and
-
will be developed using the OpenFOAM toolkit. A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition
-
MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical inventory, a major incentive for the project is the application and