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problems in health data science. Air pollution is composed of several different environmental pollutants, for example particulate matter (PM10 and PM2.5), ozone (O3), nitrogen dioxide (NO2) and sulphur
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diversity and to creating an inclusive working environment. We believe this can be achieved through attracting, developing, and retaining a diverse range of staff from many different backgrounds who have the
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with statistical modeling (ideally Bayesian statistics) • Proficiency in Fortran, R, Python, Matlab, or ideally other common languages (e.g., C/C++) Strong computational skills Strong oral and written
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projects, including: The post-holder will run numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models will be used, in Bayesian inference frameworks
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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Overview St. Jude is where those with a passion for making a difference come to break new ground. Located in Memphis, Tennessee, the mission of St. Jude Children's Research Hospital is to advance
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ML work, and allows attacking new applications which make a difference, for instance in scientific research. Different team members have different expertise, and by working together are able to address
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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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methods, Bayesian statistics, and/or an interest in applied empirical problems. We are particularly interested in candidates with expertise in applications of artificial intelligence in marketing
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, data mining, Bayesian methods, and statistical learning About Working at the Crick Our values We are bold. We make space for creative, dynamic and imaginative ideas and approaches. We’re not afraid to do