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Field
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Job Purpose Working with Prof. Surajit Ray, you will contribute to several projects involving the development of statistical models and deep learning framework for multimodal and dynamic medical
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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media including Facebook, Twitter, Instagram, YouTube, LinkedIn, and TikTok as well as excellent understanding of algorithms and platform best practices. - Storyteller at heart with strong writing skills
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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the use of quantum computers, and especially fault-tolerant quantum computers, for high-value decarbonisation use cases such as improved battery chemistries, the development of new catalysts for hydrogen
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of Excellence for Data-Driven Discovery, applying advanced computational techniques to develop novel therapeutics. This position will work closely with researchers in the Center of Excellence for Data Driven
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involves analyzing data obtained by cosmological surveys such as DESI, Euclid, Roman and others, developing new methods and algorithms, supporting other group members in particular graduate students, and
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of the Environment (ASE), and the School of Electrical and Electronic Engineering (EEE), helping to develop algorithms and systems for disaster mapping and climate change in collaboration with space industries and
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing