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directly to parallel activities at UAntwerp on LVDT sensor development and a MIGA-based local suspension platform, providing an opportunity to feed control- and sensor-level improvements developed in-house
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transition-metal complexes. The project will involve the reaction development, mechanistic studies, and synthetic applications. The postdoctoral associate will perform parallel reaction condition screening
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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empirical evidence. The project runs for 33 months and comprises three research components operating in parallel, each led by a postdoctoral researcher and integrated through monthly team meetings and
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empirical evidence. The project runs for 33 months and comprises three research components operating in parallel, each led by a postdoctoral researcher and integrated through monthly team meetings and
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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sphingolipid transport systems. You will determine high resolution single particle cryo-EM structures of sphingolipid transporters. In parallel, you will assess sphingolipid-transporter interactions and the role
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interact with parallel experimental work (EEG, eye-tracking, pupillometry) conducted within the same project. What we are looking for; we are particularly interested in candidates with a background in
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knowledge in parallel/GPU computing. Job Duties Job Duty Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research