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simulations to improve on existing power usage models. This research will be a key component of making computing more sustainable by providing novel insights into the energy usage of scientific software and
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-fast, low-energy optical interconnects in collaboration with Microsoft and two Finnish SMEs. The project focuses on development new optomechanical control methods for macroscopic quantum states of light
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
possess sufficient breadth or depth of knowledge in the discipline and of research methods and techniques to work within own area. The candidate will also have the ability to continually update knowledge
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’ opportunities and agency, using qualitative and creative methods (e.g. “Theatre of the Oppressed” or others). Please note - this position includes full funding for PhD tuition fees (UK rate) for a duration of
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. The developed technology will be rooted in causal reasoning, and we envision leveraging causal generative AI methods to develop a rigorous and comprehensive AI testbed. Clinical applications include, but are not
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-fast, low-energy optical interconnects in collaboration with Microsoft and two Finnish SMEs. The project focuses on development new optomechanical control methods for macroscopic quantum states of light
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academic performance in undergraduate and, where applicable, Master’s coursework Advanced programming skills in R and Python Familiarity with econometric techniques, especially panel data methods Ability
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discovery process, leading to more economic and effective drugs that can significantly improve the health and lifestyle of millions. The resulting methods are also expected to have an impact in materials
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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biology, and biochemistry. Plan, conduct, and contribute to experimental work. Identify and develop relevant methods for data collection, analysis, and interpretation. Develop expertise across scientific