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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put on discovering biophysical
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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work with large-scale behavioural data sets using a range of approaches, including heritability analyses and machine learning. Some data for the project already exist, but additional data will be
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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Job Description Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges? Responsibilities and
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating