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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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for producing high quality research outcomes in the area of animal behaviour. This project involves establishing and imaging butterfly courtship interactions within experimental enclosures with the ultimate aim
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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approaches - including molecular genetics, RNA sequencing, FACS, biochemistry, confocal imaging, and behavioral analyses - along with integrative -omics workflows. Applicants must be able to apply
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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control in neuronal synapses You will be working with primary neuron cultures, rodent in vivo models, and patient brain biopsies You will use advanced microscopy for super-resolution and live imaging
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18 Oct 2025 Job Information Organisation/Company UNIVERSITY OF SOUTHAMPTON Research Field Engineering Researcher Profile First Stage Researcher (R1) Country United Kingdom Application Deadline 20
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biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering, Data Science, Bioengineering or Applied Mathematics