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As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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Postdoctoral Research Associate - Training in Pediatric Cancer Survivorship Outcomes and Interventio
biology, psychology and neuropsychology, neuroscience, exercise physiology, oncology, pharmacology, radiology, surgery and biostatistics. St. Jude leads two of the world's largest pediatric survivorship
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are readily available, including biorepository and clinical biomarkers labs, biostatistics, applied bioinformatics, proteomics and metabolomics and a variety of brain and body imaging resources (MRI, fMRI, DTI
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(LC-MS) and focusses on biostatistical analysis of the obtained protein expression profiles and the experimental validation of the findings in tissue sections. Your Profile We are seeking a highly
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Do you want to contribute to top quality medical research? The Department of Medical Epidemiology and Biostatistics conducts research in epidemiology and biostatistics across a broad range of areas
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Strong theoretical background and practical experience in neurosciences, with a keen interest for neurometabolism Solid bioinformatic and biostatistics skills will be required Excellent organizational and
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manuscripts Preparation of grant applications Providing guidance to junior researchers Your profile: A PhD degree (or comparable) and a strong background in biostatistics, epidemiology, biology, medicine
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. Requirements Essential Requirements PhD Degree in a relevant scientific field (e.g. genetic epidemiology, molecular epidemiology, statistical genetics, biostatistics, health data science, etc) to be obtained max
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Computer science, Biostatistics, Bioinformatics, Neuroscience, or similar field. Proficiency in written and spoken English. Previous work with large-scale data analysis, integration and visualization. Proficiency in