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Field
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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capabilities. Experimental design, laboratory execution, data analysis, and statistical quality control. Required Education PhD Degree in Biochemistry, Molecular Biology, Molecular Genetics, or closely related
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and maintenance Participate in team meetings and present research findings to internal and external stakeholders Minimum Qualifications PhD in Chemical Engineering, Materials Science, Electrochemistry
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be offered health and dental insurance and other benefits. He/she will have access to all research and training resources available at the University of Utah and to the postdoctoral training programs
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(IRACDA) program . This comprehensive program offers 3 years of support to outstanding candidates seeking postdoctoral research training along with an opportunity to obtain mentored teaching experience in a
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analyse data, interpret and present results to a high standard using a range of specialised research techniques. Good knowledge of the R statistical programming language. Programming experience in C, C
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. Preferred: • Strong programming skills in languages such as R/Python • Research background in biostatistics/statistical genetics/population genetics/deep learning and LLM • Experience in any of the following
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in Mathematics, Statistics
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environment that fosters a culture of inclusivity and teamwork. - Engage in ongoing academic and intellectual life within CALS and Cornell University. Requirements • PhD in ecology, quantitative ecology