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innovations, and connect their work to the broader community. This unique program is open to all current PhD students at Tandon School of Engineering who will defend their dissertations by September 1, 2026
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative research may include but is not limited to software tool dissemination, biology discovery, and
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start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute from the onset. You will liaise with external collaborators and
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with PhD and master students and with medical doctors. You will start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
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the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group
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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces