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of novel strategies for neuronal analysis in health and disease and optimizing novel methods. The project is funded by My Name’5 Doddie Foundation, as part of their Catalyst Awards. Using iPSC-neurons, our
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
, and Fagales. Research Focus While the two positions will work closely together and share many responsibilities, they have slightly different initial focus areas: Position 1: Computational Genomics and
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data to refine objective measures of neural function and improve clinical strategies for hearing aid optimization in this population. References: [1] A. Starr, T. W. Picton, Y. Sininger, L. J. Hood, and
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. Proficiency in programming MATLAB and Python for data analysis and algorithm development. Knowledge of data assimilation techniques is a valuable added. Excellent communication skills and ability to work
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Duties and Responsibilities: -You will be responsible for performance of routine quality control (QC) testing such as bioburden, endotoxin, and microbial ID analysis. -In this context, you might be
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Brief Summary of Work for this Position The College of Science and Engineering at University of North Carolina Wilmington invites applications for a postdoctoral scholar to begin Fall 2025. A UNCW
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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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The Role Applications are invited for a two-year full-time Postdoctoral Research Associate position beginning around October 2025 (although there is some flexibility in this date, in both directions
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that are motivated to help each other are highly encouraged to apply. Please describe in your summary of current work what type of analysis and tools you would like to develop in the lab, based on your previous
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical