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approaches in research design and data analysis, including: Advanced biostatistics and epidemiology, Applications of artificial intelligence and machine learning, and Leveraging diverse data sources (e.g
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experience in Biomedical Engineering who has a critical eye, a deep understanding of their subject and interests beyond, and who can think on their feet. Knowledge of machine learning is desirable although we
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analysis Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability of experimental
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal behavior and neuronal activities in circuits of murine models of 22q11.2 and
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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Center for Neurocomputation and Machine Intelligence. WTI enables interdisciplinary inquiry through fellowships for co-mentored postdocs, grad students, and undergrads; shared research facilities and
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more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ The candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with specialisation
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, CNRS, I3S, Sophia-Antipolis, France) Collaboration: Luca Calatroni (Luca.calatroni@unige.it), Machine learning Genoa Center, Italy. Context and Post-doc objectives Conventional optical microscopy
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such as causal inference or machine learning or complex panel data analysis. We are seeking excellent applicants with an international research portfolio and network. The teaching portfolio includes courses