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Postdoc position in method development in human statistical genetics, with a focus on classificat...
University. Dr Speed's research involves developing statistical methods for better analysing data from genome-wide association studies (GWAS), with a particular focus on improving our understanding of human
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the project and in collaboration with the team Contribute to outreach and impact engagement activities of the project Identify appropriate sources of funding and help prepare research proposals for funding
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Particle Physics, Astro particle Physics and Cosmology, as well as for developing state-of-the-art instrumentation under the framework of several international scientific collaborations and medical physics
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will develop numerical procedures in
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through joint publications with the project's research team. The candidate will be invited to develop strategies for analysing the various forms of proximity (geographical and cognitive), and will propose
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data. Prepare results for presentations, reports, and publications. Maintain all required training and certifications. Requirements: PhD Duke is an Equal Opportunity Employer committed to providing
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods
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contribute to a project that will develop and analyse computational models for electricity markets, the power system and hydro power scheduling. The position will be affiliated with the ENE Centre at the
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GC-MS and the postdoctoral associate will make the measurements, analyze the data, prepare manuscripts, and present the results at conferences. There will be opportunities for mentoring student
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empirically the historical evolution of political cleavages and socioeconomic inequalities, with a multidisciplinary perspective and the use of granular local level data and cutting-edge statistical methods