58 parallel-processing-bioinformatics-"IMB" Postdoctoral positions in United Arab Emirates
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undergraduate students. The ideal candidate will have a Bachelor’s degree in Biology, Genetics, Bioinformatics, Evolutionary Biology, Microbiology, or a related field, and a strong background in microbiology
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, Bioinformatics, Evolutionary Biology, Microbiology, or a related field, and a strong background in microbiology, microbial genetics, natural product chemistry, or related fields, and hands-on experience with
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undergraduate students. The ideal candidate will have a Bachelor’s degree in Biology, Genetics, Bioinformatics, Evolutionary Biology, Microbiology, or a related field, and a strong background in microbiology
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underlying mental processing speed. The successful applicant will drive a fascinating project that links processing speed measures to previously acquired functional and structural MRI data. The project will
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for Brain & Health, New York University Abu Dhabi, seeks to recruit a Post-Doctoral Associate to work on the mechanisms underlying mental processing speed. The successful applicant will drive a fascinating
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. Strong publication record in top-tier venues. Solid background in one or more of the following: Query processing or optimization Constrained or combinatorial query evaluation Data modeling under
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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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Computer Science or a related field, with a focus in databases, data systems, theory, or algorithms. Strong publication record in top-tier venues. Solid background in one or more of the following: Query processing
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process for sustainable transport modes and transport innovations. Research is interdisciplinary involving behavioral economics, psychology, neuroscience, computer science applied to the transport domain
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems