Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- Swedish University of Agricultural Sciences
- Umeå University
- Uppsala universitet
- SciLifeLab
- Lunds universitet
- Karolinska Institutet, doctoral positions
- Lulea University of Technology
- Umeå universitet
- Chalmers University of Technology
- Luleå tekniska universitet
- Luleå university of technology
- Nature Careers
- Stockholms universitet
- Institutionen för molekylära vetenskaper
- Linköpings universitet
- Lule university of technology
- Mid Sweden University
- Mittuniversitetet
- Mälardalen University
- Sveriges Lantbruksuniversitet
- University of Borås
- 12 more »
- « less
-
Field
-
biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will you be part of that change? Then join us in
-
-language-action models (VLA), specifically the handling of uncertainty in VLAs. VLAs have the potential to simplify system design in robotics and autonomous driving, both through verbal user interfaces, and
-
Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
-
methods that can accurately model such processes remains an open and active research frontier. This PhD project is fundamentally about advancing that frontier, contributing new methods for generative
-
microstructural descriptors that are physically meaningful and predictive. Probabilistic surrogate modelling and digital twin construction. The extracted microstructural descriptors will be used to learn a
-
increasingly rely on data-driven models to extract, represent, and interpret information from complex and evolving environments. Traditional machine learning approaches, as well as many classical signal
-
biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will you be part of that change? Then join us in
-
. Research will have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or
-
research is conducted on wild species, agricultural crops, forest trees, bioenergy crops, and model organisms. Our main research areas include genome analysis, the interactions between plants and
-
. You would be welcomed in the the Yant Lab (https://www.yantlab.net/ ) Using large-scale graph-based pangenomics and forward evolutionary simulations, the student will develop predictive models