Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Umeå University
- SciLifeLab
- Lunds universitet
- Uppsala universitet
- Linköping University
- Stockholms universitet
- Chalmers tekniska högskola
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Umeå universitet
- Blekinge Institute of Technology
- Karolinska Institutet (KI)
- Linköpings universitet
- Luleå University of Technology
- Nature Careers
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Karlstad University
- Linköpings University
- Linnaeus University
- Malmö universitet
- Sveriges Lantbruksuniversitet
- University of Lund
- Örebro University
- 15 more »
- « less
-
Field
-
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
-
, we aim to generate knowledge towards the development of sustainable pest and disease management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can
-
and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant production systems. Within the Landscape Planning group at the Department of Landscape
-
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
-
the development of sustainable pest and disease management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant
-
management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant production systems. Read more about our
-
, 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