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data storage capacity to accelerate research in intensive computing and large-scale data analytics, commonly referred to as Big Data. This characteristic distinguishes the HPC center at the university
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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, and advanced data analysis. This role is part of a large-scale, multi-institutional consortium study aimed at uncovering novel insights into the genetic and molecular underpinnings of neurodevelopmental
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data and high-throughput, multi-dimensional -omic data to study neurodegeneration and diseases of the central nervous system, with an emphasis on Alzheimer disease, Parkinson’s disease, and other
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-precision vertexing and tracking of charged particles. Past and current projects include the upgrades of the Inner Tracking System (ITS) for the ALICE experiment at the Large Hadron Collider (LHC) at CERN
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. Integrate deep mutational scanning data to assess viral fitness and immune escape, collaborating with experimental virologists. Work with large-scale genomic and proteomic datasets from BV-BRC, GISAID, and
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management tools. This role involves designing and executing large-scale epidemiological studies using EHR data, overseeing clinical data annotation/processing from public and Hospital Authority sources, and
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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complements LCAB’s research programmes. High competence in the analysis of large ecological and other data sets and time series. Ability to write up research for publication in high profile journals, along with
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a