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collaborative research environment that exemplifies IDAI's distinct approach to interdisciplinary data science and AI research. Person Specification PhD (or near completion) in Computer Science, Data Science, AI
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of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing
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modeling of the data. The successful applicant will join a vibrant research group that uses a wide variety of spectroscopic methods to study photochemical processes. Essential Duties and Responsibilities
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Supervise students on research-related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake
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outcomes using design practices. The role is to contribute to a programme of research in partnership with Glasgow University and Glasgow Centre for Population Health to co-develop Community food markets as a
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goal of this project is to perform a coherent control experiments with a levitated particle, in the classical and ultimately in the quantum regime. We ultimately aim to generate experimental methods
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of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing on gene regulation and the engineering of microbial and human cells. You
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spectroscopic data analysis. This role forms part of a larger research effort exploring advanced polymer processing techniques and data driven methods to improve material performance and manufacturing efficiency
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sufficient breadth or depth of research methodologies to work in the research area; ability to contribute to method improvement; analytical ability to facilitate conceptual thinking, innovation and creativity
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with international colleagues. Developing new qualitative coding and assessment frameworks. The role holder will have the opportunity to use their initiative and creativity to develop research methods