Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- Swedish University of Agricultural Sciences
- Umeå University
- Institutionen för akvatiska resurser
- LInköpings universitet
- Linköpings universitet
- Lulea University of Technology
- Luleå university of technology
- Lunds universitet
- Stockholms universitet
- Swedish University of Agricultural Science
- Umeå universitet
- Uppsala universitet
- 3 more »
- « less
-
Field
-
principled new models and methods, for modern machine learning problems. Machine learning recently has been largely advanced by differential equation-based frameworks, such as generative diffusion models
-
://elliit.se ) and focuses on enabling reliable robot situational awareness in challenging and unpredictable environments. The project is grounded in statistical, model‑based methods that combine multi‑object
-
) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
-
application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
-
model-based methods, the project enables systems that can detect, distinguish, and track multiple simultaneous events or objects using sensor information from, for example, radio, audio, and vibration
-
allocation is of particular interest when a vehicle has multiple ways of being controlled (redundant actuators), where each method has its own advantages and disadvantages regarding factors such as radar
-
the flexibility of neural methods. If successful, the work has the potential to advance applications such as automated theorem proving, knowledge-graph inference, and causal analysis. The Department of Computing
-
for estimating plant population size and change Mathematical statistics Description: We are looking for a dedicated and goal-oriented PhD student who wants to contribute to the development of methods
-
on the intersection of robotics and control theory. Project description: This PhD project aims to develop learning‑based methods that combine expert demonstrations with experiential reinforcement learning to enable
-
of the sea, with a focus on questions related to marine protected areas About the position You will primarily work on developing and applying video-based methods for monitoring fish in protected areas and