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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
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of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high
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Infrastructure? No Offer Description The selected candidate will lead the metabolic modeling efforts within our Biotechnology pillar. The primary goal is to use computational modeling and network analysis
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sequencing or draft genome sequence analysis, is highly desirable. Project title: Gut microbiome and health Duration: 12 months, full-time post Please note that Garda vetting and/or an international police
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synthesis. · Experience in LC-MS and LC-MS/MS analysis · Experiences in SDS or fluorescence gel electrophoresis, tryptic digestion and any other proteomic technique. We offer · A full-time contract for three
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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questions related to artificial intelligence, sentiment analysis, social networking analysis, marketing and management strategy, public policy, marketing data modelling, consumer behavior, and online
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platforms, security analysis, adversarial AI attacks and defences, intrusion detection, load management in mobile edge networks, or denial-of-service detection are considered as a merit. Earlier experience in
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 hours ago
organoid culture methods. Experience in computational analyses of proteomics or single-cell sequencing datasets. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary
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possible research topics include: (i) social media analysis, (ii) collaboration and teamwork, (iii) gender inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal