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Field
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industry to facilitate and coordinate new research collaboration and initiatives Proficiency in relevant programming, data analysis and modelling tools (e.g., Python, AI/ML, Simulation software – SUMO, Agent
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climate resilience. Working within a world-class research environment, you’ll combine your skills in plant and crop physiology, modelling, phenotyping, data science, and statistics to uncover insights
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Observatory of Japan (NAOJ, under JSPS-KAKENHI International Leading Research (ILR) program; 22K21349) co-funded position offers a unique opportunity to work at the intersection of astronomy, optics, and
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computational and theoretical analysis using a range of techniques, as well as collaborating with the other members of the wider project team. To be successful in this position, you will have: PhD qualification
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Brown. The position will be responsible for drafting data collection tools, coordinating feedback with study partners, co-facilitating the system mapping workshops, descriptive model development and
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the other members of the wider project team. To be successful in this position, you will have: PhD qualification in the relevant discipline area, such as computational/theoretical physics or chemistry, or
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these data with multi-omics datasets to identify regulatory or metabolic bottlenecks. It involves statistical analysis and systems modelling, and close collaboration with strain engineering and bioprocess
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of these publications and your part in these. Selection Criteria: Essential PHD in Computer Science, Informatics, Data Science, Statistics, or a closely related area. Substantial research experience in applied Artificial
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responsible for drafting data collection tools, coordinating feedback with study partners, co-facilitating the system mapping workshops, descriptive model development and testing with sector stakeholders. It
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intracellular signalling, including design of experiments, analysing data, writing manuscripts and reports, and supporting grant applications. This position will fit into a multidisciplinary environment with