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University. Key Responsibilities: Conduct project related research on geophysical/geomechanical investigation, geomodelling, data analytics, and machine learning. Responsible for processing and analyzing
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Research Fellow will work closely with the Lead PI in carrying out in-depth research to deal with huge volume of real-time rich multi-model data, scalable big data analytics and re-examine the role of man
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, validate, and harmonize field and remote sensing imagery for ecosystem monitoring. Develop machine/deep learning-based workflows to interpret ecosystem disturbance. Synthesize model simulations and
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developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their
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, machine learning, data science, drug discovery, and related fields are encouraged to apply. Strong computational backgrounds (AI/ML foundation models), proficiency in at least one programming language
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sensing, computer vision, mental health, data fusion, computational medicine, predictive analytics, big data, neuroscience, and related fields. AI + Life Sciences: Participate in research projects that
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boundaries helps us to turn our science into benefits for human health and the economy. About the Fröhlich Lab The Fröhlich Lab combines quantitative biology with scientific machine learning (SciML
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genetics/genomics, bioinformatics, machine learning, data mining, and computational programming, including software or package development. The ideal candidate will hold a PhD in bioinformatics or
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to develop a biophysically interpretable machine learning model that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenetic features, and three-dimensional
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Lab – leaders in generative AI and foundation models for spatial and single-cell genomics – you will develop and apply state-of-the-art machine learning approaches to large-scale spatial genomics and