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Excellent organizational skills and ability to plan effectively Experience performing divergence time estimation (e.g., using BEAST), and biogeographic modelling (Desirable) A track-record of publications in
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outline how you meet the essential criteria of the role and evidence this with examples. Key Accountabilities Contribute to the research programme in the field of Bayesian computational statistics as part
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program aiming to transform the UK’s wastewater treatment processes through detailed microbial understanding and optimization. You will work closely with a highly experienced PDRAs in Newcastle and
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with your experience level, is also desirable. You will also be encouraged to participate in the group’s vibrant outreach programme. This role has secured funding until June 2027. Please contact Prof
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activities such as workshops and impact-oriented events. This is a unique opportunity to inform the work programme of an exciting new interdisciplinary centre for Joined-Up Sustainability Transformations
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activities such as workshops and impact-oriented events. This is a unique opportunity to inform the work programme of an exciting new interdisciplinary centre for Joined-Up Sustainability Transformations
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Newcastle Drug Discovery Programme and as a partnership with Cancer Research Horizons and Astex Pharmaceuticals. It is ideally suited to candidates with a background in organic chemistry, medicinal chemistry
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Experience implementing mixed-integer, conic or nonlinear programming and modelling frameworks (JuMP, Pyomo, Yalmip, GAMS, etc) Experience with unbalanced distribution system analysis tools (e.g., OpenDSS
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responsibilities expected of role holders at each level and secondly the general qualifications and experiences needed for entry at a particular level. Key Accountabilities Contribution to the research programme of
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for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program