86 modelling-complexity-geocomputation Postdoctoral positions in United Arab Emirates
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communications Hardware-constrained signal processing for wireless communications Channel modeling and characterization Applications will be accepted immediately and candidates will be considered until
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and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal candidate will have a strong interest in applying these tools to questions of group
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conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic, multidisciplinary environment alongside PhD-level engineers and scientists, graduate students, and full-time
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the frontiers of developmental biology and disease modeling. The laboratory integrates stem-cell biology, fluorescence imaging, bioinformatics, and advanced nano- and micro-engineering to decode organogenesis and
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, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be
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hypothesis generation in finance / natural sciences / physical sciences, enhancing collaborative workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer
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implement innovative solutions. He/she will contribute to the development of novel concepts and proposal writing, while efficiently addressing complex challenges. Responsibilities will include writing reports
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and metabolic disorders. These approaches entail device design and manufacturing, drug conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic
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adaptable object handling in complex real-world scenarios, including those involving deformable objects and uncertain conditions.. Semantic Navigation & Mapping – Designing solutions for robot navigation
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation