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classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high-throughput, automated analysis of large image datasets from fluorescence
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
loss patterns across diverse plant lineages Explore graph-based algorithms for multiple genome alignment and ancestral karyotype reconstruction Position 2: Evolutionary Analysis and Network
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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top 10 IT security/crypto conferences) Strong mathematical and algorithmic CS background, economics/finance - a plus Good skills in programming and scripting languages Commitment, team working and a
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/non-convex optimization (Mandatory) Signal processing Computational electromagnetics focused on time domain algorithms (Mandatory) Programming skills in MATLAB (Mandatory) Good oral presentation skills
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Mobility (UAM) Experimental emulators, prototypes, testbeds and distributed research infrastructure test platforms Set up real-world testing both in the laboratory using emulators and software defined radios
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including other forms of 'smart' automation, such as algorithmic recommendation and chatbots. We are hiring a postdoctoral researcher to develop a project critically analyzing the role of AI in media and
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to study effects of (TI)-DBS on ex vivo brain slices and in vivo rodent models. Develop advanced closed-loop neurostimulation algorithms. Engage in a cross-disciplinary team, collaborating with experts