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National Food Institute. We are currently developing a massive web application for users world-wide to store and share their sequencing data as well as running bioinformatics pipelines to analyse and
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the data's structure, which can reveal hidden patterns. The project aims to apply and adapt TDA techniques from various fields—such as physics, mathematics, bioinformatics, and neuroscience—to uncover new
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Bioinformatics, Computational Biology, Systems Biology, Computer Science, or related field. Demonstrated experience with data analysis generated by NGS, proteomics, single-cell omics and spatial genomics. Strong
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
and teaching. The Stellos Lab at the Department of Cardiovascular Research is seeking for a permament full-time position a highly motivated and talented Senior Scientist / Group Leader on Bioinformatics
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and Course Number: Using Bioinformatics Resources - HGEN 693 Name of the Course Coordinator: Prof. Claudia Kleinman Estimated Number of Positions: 1 (One) Total Hours of Work per Term: 100 hours per
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: Privacy, Ethics, Regulation & Policy Introduction to Artificial Intelligence Predictive Modeling and Machine Learning Image Processing and Deep Learning Bioinformatics & Biomedical / Clinical Data Analysis
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ovarian cancer research. The appointed candidate will have bioinformatic expertise, including experience using R and/or Python. High attention to detail is essential, as well as an ambition to produce high
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relevant field of Biology. Experience of benchwork in molecular biology or bioinformatics. Preferred Qualifications Degrees in Neuroscience or Genomics. Demonstrated ability to work collaboratively within a
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Food Institute. We are currently developing a massive web application for users world-wide to store and share their sequencing data as well as running bioinformatics pipelines to analyse and visualize
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hidden patterns. The project aims to apply and adapt TDA techniques from various fields—such as physics, mathematics, bioinformatics, and neuroscience—to uncover new insights and improve ML models. By