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Field
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. More generally, the PhD thesis is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of machine learning systems by providing industry actors with practical tools
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, Machine Learning, or Smart Energy Publication record in peer-reviewed journals or conferences, commensurate with stage of career Good programming skills in Python, R, Java, or Matlab Experience
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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, stroke rehabilitation, and chronic disease prevention. The PhD student will work in an interdisciplinary team spanning behavioural scientists, clinical psychologists, computer scientists, AI engineers, and
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to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and
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, Microelectronics, Computer Engineering, or a closely related field, completed by the start of the position Have a solid background in digital hardware design: Verilog/SystemVerilog RTL, logic synthesis, and place
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data engineering and management; machine learning and data-driven modelling as well as Digital twins and hybrid physics - (agentic)AI approaches. Experience in the industrial environment is considered
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processes. • Apply machine learning techniques and advanced statistical analysis to extract knowledge from complex datasets. • Participate in the evaluation and optimisation of high-performance scientific
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance