603 data-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Fellowship positions in United Kingdom
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for generating data for associated research publications and other forms of dissemination. The majority of the analytic work will be stable-isotope tracer-based mass-spectrometry to assess changes in muscle
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portfolio. You will be required to have strong organisational and data analysis skills. You will be expected to plan and conduct work using approaches or methodologies and techniques appropriate to the type
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independent verification of unspent convictions obtained by means of a Basic Disclosure Certificate obtained from Disclosure Scotland, or an overseas police check. Further information is available in the role
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to root patterning. Integrate molecular and imaging data into a spatio-temporal developmental framework. Research environment and approaches The project is highly interdisciplinary. The successful candidate
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in research, data analysis and stakeholder engagement. You will demonstrate initiative and the ability to work both independently and as part of multidisciplinary and international teams. Experience
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of effective & efficient healthcare interventions. You will design and deliver cost-effectiveness and budget impact analyses, analyse healthcare cost and outcomes data, and develop decision-analytic models
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applicant will participate in ongoing projects on microorganism motility that are relevant in a range of ecologically significant contexts, combining experimental biophysics, quantitative data analysis and
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within the Institute. This role is suitable for individuals who hold, or will have been awarded by the start date, a PhD/DPhil in AI Ethics and/or Data Ethics and/or Neuroethics and/or Philosophy
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through innovative automation, analytical science, and data-driven optimisation. You will upgrade a self-optimising flow reactor modular platform integrated with high-throughput experimentation (HTE) and
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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels