Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Forschungszentrum Jülich
- Basque Center for Applied Mathematics
- CNRS
- Eindhoven University of Technology (TU/e)
- Institut Pasteur
- KU LEUVEN
- Massachusetts Institute of Technology (MIT)
- Newcastle University;
- Swansea University;
- University of Birmingham
- University of Cambridge
- University of Massachusetts Medical School
- University of Sheffield;
- University of Warwick
- 4 more »
- « less
-
Field
-
, optimization, dynamic systems, decision theory, Bayesian inference) ● Is motivated to apply these methods to ecological, evolutionary, and conservation systems; ● Is comfortable with uncertainty, modeling
-
close to the nest [1 ] but to better understand foraging, we need landscape level detail. The direction of the project can be tailored, but could include developing and applying Bayesian ML approaches
-
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
-
behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
-
processes related to carbon cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset Ability to work independently and cooperatively as part of an interdisciplinary