Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- Linköping University
- Lunds universitet
- University of Lund
- Umeå University
- SciLifeLab
- KTH Royal Institute of Technology
- Uppsala universitet
- Jönköping University
- Lulea University of Technology
- Karlstad University
- Linköpings universitet
- Göteborgs Universitet
- IFM/Linköping University
- KTH
- Karolinska Institutet, doctoral positions
- Luleå University of Technology
- Mälardalen University
- Nature Careers
- Sveriges Lantbruksuniversitet
- Umea University
- Umeå universitet
- Umeå universitet stipendiemodul
- University of Borås
- 14 more »
- « less
-
Field
-
review. The research question for the work package is: How is public communication about the Swedish energy transition shaped on algorithm-driven platforms in the meeting between globalised nationalist
-
nomenclature, standardize laboratory test methods and result vocabularies, and translate clinical and laboratory free text into structured terminology. The project combines classical text algorithms, medical
-
of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
-
We are seeking a postdoc to co-design efficient and realistic simulation algorithms for noisy quantum circuits in superconducting hardware, combining quantum modeling with hardware-aware performance
-
for strings. *for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted. The following experience will strengthen your application: Course work in bioinformatic algorithms
-
algorithms for resource-efficient learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce
-
precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
-
tree. In fact, the problem being NP-hard, a handful of aircraft is enough to make it unsolvable in polynomial time. The work requires theoretical studies on the state of the art, together with algorithm
-
models and algorithms in Python, with documented experience in PyTorch. The applicant should be knowledgeable with neural networks and furthermore have a strong drive towards performing fundamental
-
logical perspectives. Key areas of interest include proof complexity, circuit complexity, communication complexity, meta-complexity, and their connections to algorithms. Lund University is located in