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University of Massachusetts Medical School | Worcester, Massachusetts | United States | 2 months ago
. Preferred qualifications: D. in Quantitative Genetics/Genomics, Computational Biology, or Related Discipline. Skilled in single-cell transcriptomic analyses, machine learning and artificial intelligence
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6. of this Notice. Preferred factors: Knowledge in machine learning and programming (Python), deep learning (e.g., tensorflow, pytorch) and time-series modeling in marine ecology applications
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consider novel design principles combining approaches in biosensors, communication systems, and machine learning. Are you motivated to take a step towards a doctorate and open up exciting career
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GNSS, wireless navigation and machine learning is desirable Additional skills that are highly appreciated in this position are the willingness to work hard and to learn more about the fascinating
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synthetic biology, machine learning (ML), and ultrahigh-throughput screening (microfluidics) to discover new enzymes and bioactive molecules with applications in biotechnology, medicine, and sustainability
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to be made in accordance with NTNUs guidelines for recruitment positions and Regulations for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the
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that combine principled reasoning with the efficiency of modern machine learning to enable intelligent, real-time decision-making in large-scale interconnected systems. This position offers the opportunity
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eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please contact the hiring
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Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data