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highly recognized research. More information about us, please visit: The Department of Biochemistry and Biophysics . Project description The successful candidate will develop machine learning (ML
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years of research experience in biology or a related discipline. Publication record demonstrating computational skills in image processing or genomic data analysis. Proficiency in rodent neurosurgeries
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to validate theoretical approaches, utilizing machine learning techniques to derive meaningful conclusions. Collaborative Projects: Engage in collaborative research with interdisciplinary teams, contributing
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. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health, bio-signal processing, and wearable
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simulation or machine learning of soft and biological matter, e.g. Monte Carlo, molecular dynamics and finite element computer simulations. Origins of life research involving topology and chirality
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PyTorch, TensorFlow, and Scikit-learn. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health
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ATAC sequencing, spatial transcriptomics, proteomics, whole-genome sequencing, functional screens, bioinformatics, and/or data algorithms including machine learning will be given preference. A successful
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be disseminated through academic publications and online webinars. The successful candidate will have a PhD in human-computer interactions or computer science and related fields, with demonstrable
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machine learning for real-world applications. Scalable Digital Health Solutions: Develop methodologies for reliable, long-term motion monitoring across diverse user groups and environments
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single synthetic program of computational geometry. Specific interests include morphology, design topology, discrete differential geometry, packings, and machine learning methods for unstructured geometric