Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- University of Lund
- Linköping University
- Lulea University of Technology
- Nature Careers
- Umeå University
- SciLifeLab
- Stockholms universitet
- Swedish University of Agricultural Sciences
- Uppsala universitet
- Blekinge Institute of Technology
- KTH
- KTH Royal Institute of Technology
- Karlstad University
- Linnaeus University
- Mid Sweden University
- Mälardalen University
- Umeå universitet stipendiemodul
- University of Gothenburg
- Örebro University
- 10 more »
- « less
-
Field
-
Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
-
/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
-
exists for researchers to design and improve animal tests. These limitations hinder the development of optimal experiments and incur cruel animal suffering and killing.The position is two years and you
-
of research that has been developed at the Unit is the proposal and computational implementation of novel formulations for the conceptual design of mechanical components and structures via topology optimization
-
of hyperdimensional computing and vector symbolic architectures (VSA). As a Senior Research Engineer, you will: Implement, optimize, and run simulation code in Matlab and Python. Develop lab assignments for upcoming
-
Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
-
, including finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks
-
algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
-
. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
-
the optimal design of social support systems. The PhD position primarily concerns the part of the program that studies how AI changes the organization of work and employees. The program currently includes 12