Sort by
Refine Your Search
-
Employer
-
Field
-
experience in radar research, developing signal processing algorithms for long-range ultra-broadband Synthetic Aperture Radar systems and short-range FMCW systems. In recent years, breakthroughs in
-
at the Faculty of Engineering and contribute to cutting-edge research in radar systems. The radar group at BTH has extensive experience in radar research, developing signal processing algorithms for long-range
-
develop new algorithms where needed: this may include the incorporation of genomic or other omic data 2) An important second part of the post is helping to automate components of interpretation and
-
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
-
optimization approaches will be developed. Main responsibilities Your major responsibility as doctoral student is to pursue your own doctoral studies. You are expected to develop your own scientific concepts and
-
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
-
Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg | Sweden | 14 days ago
mechanisms in normal neural development (demonstrated by us and colleagues) and may harbor cues for novel treatment strategies. Omics data can be used in black box machine learning algorithms to classify or
-
environments. This research direction demands developing novel techniques and algorithms that can enable effectively integrating sensorimotor information with learning algorithms, and, at the same time, leverage
-
. The research team focuses on developing novel methods to extract knowledge from data, modeling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but