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species including dairy cattle in the USA; this large reservoir of infection has substantial implications for both human and animal health. Using a range of modelling and statistical approaches
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related discipline (Neurobiology, Computer Science, Statistics, Epidemiology, Systems Biology, Computational Biology). ● Proven research track record with publications or preprints in relevant domains
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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis
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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications
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communication skills Strong logistical coordination skills Training in advanced statistical techniques and computational methods Experience managing and analyzing large, administrative datasets The ability to balance
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-class biologists in the Harvard medical area. Basic Qualifications An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field. Superb
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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administration or data analytics, such as Applied Psychology, Organisational Behaviour, Statistics, Machine Learning, and so on; Excellent oral and written communication skills in English, including the ability
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and California and identify locations that are potentially vulnerable to future disturbance. A plot-level statistical model will be developed to understand drivers and identify where near-term tree
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statistical inference/optimization, and will have the chance to mentor both undergraduate and graduate students in these areas (as it relates to joint projects). Special Instructions Required application