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electrochemical techniques. Experience with data visualization and analysis software. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background
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and visualization. The objectives to be achieved include the development of advanced skills in spatial data analysis, Machine Learning and applied research, as well as contributing to the production
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) supervision. There will also be opportunities to engage in data analysis and dissemination as appropriate. This position is full-time, working on campus 35 hours per week, and fixed-term for two years or until
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to characterize immune and tumor cell phenotypes. -Execute standard molecular biology techniques, including PCR, Western blotting, and gene expression analyses. -Apply confocal microscopy to visualize cell-cell and
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the
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modelling, simulation, and visualization functionalities, as planned in the European project ARTEMIS - Applying Reactive Twins to Enhance Monument Information Systems. Activities may include designing and
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systems (such as RedCAP), Endnote files, and databases Demonstrated experience with data analysis, visualization, and building machine learning models in programming language such as Python or/and R
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Proficiency in computational data analysis Strong background in system biology/molecular biology/cell biology Grade requiremens The norm is as follows: The average grade point for courses included in
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a related field who bring hands-on expertise in in vivo calcium imaging or electrophysiology, along with strong data analysis experience in Python and/or MATLAB. Candidates who combine quantitative