Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Umeå University
- Linköping University
- SciLifeLab
- Uppsala universitet
- Chalmers tekniska högskola
- Lunds universitet
- Umeå universitet
- Blekinge Institute of Technology
- Karolinska Institutet (KI)
- Linköpings universitet
- Luleå University of Technology
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Linköpings University
- Lulea University of Technology
- Malmö universitet
- Nature Careers
- Örebro University
- 9 more »
- « less
-
Field
-
comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial
-
properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
-
apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
-
analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics
-
interpretation of results. You will also tailor these analyses in response to clinical and researcher feedback, and help develop new algorithms where needed: this may include the incorporation of genomic or other
-
, or equivalent, with excellent knowledge of digital communications and signal processing. High grades in the core courses are required. Skills in mathematical analysis, modeling, and network algorithms
-
on Bayesian methods for real-time, risk-aware trajectory planning in autonomous driving. Develop, implement, and evaluate algorithms for scenario pruning, control action selection, and reachability analysis
-
driving. Develop, implement, and evaluate algorithms for scenario pruning, control action selection, and reachability analysis. Compare advanced deep learning–based methods with probabilistic approaches
-
through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and techniques to cope with real-world challenges including but not limited to uncertainty, physical
-
setting. In this environment, our research group focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are