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with experimental collaboration to uncover complex biological mechanisms. Our interdisciplinary work draws on statistical physics, applied mathematics, and close ties with experimental labs. Current
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
Experience in uncertainty quantification or statistics applied to quantum chemistry and machine learning would be advantageous For more details, please take a look at the role profile. We'll still consider
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analysis) and tumour cell injection (Desirable) Experience of using bioinformatics software and methodologies to analyze multi-omic and therapeutic datasets (e.g. R statistical environment) (Desirable
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collaboration with statistical physicists for data analysis and experimental design. The Associate is expected to generate breakthrough ideas in the assigned area of research, as well as to carry out research in
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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data independently. The post holder must also have a strong statistical background, with at least one recent publication in an internationally reputable journal. Application Process You will be required
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opportunity to work within a multidisciplinary team that includes world experts in psychology, clinical neuroscience, statistics, patient-clinician communication, and cancer survivorship care. The post-holder
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techniques. Analyse experimental data using statistical tools and computational methods. Collaboration & Mentorship: Collaborate with interdisciplinary teams of researchers and students. Mentor graduate and
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mass spectrometry (especially GC-MS) and programming (e.g. R), statistical knowledge for omic-scale research questions Scientific publishing experience in renowned, subject-relevant peer-reviewed