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- Institute of Molecular Genetics of the Czech Academy of Sciences
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-of-cellular-metabolism/ The position is for you if: …you have strong data analysis skills and enjoy working with large, complex datasets (e.g., single-cell, spatial, imaging-based or other omics data) …you have
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-of-cellular-metabolism/ The position is for you if: …you have strong data analysis skills and enjoy working with large, complex datasets (e.g., single-cell, spatial, imaging-based or other omics data) …you have
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fluorescence live imaging, and 3) conduct a genetic characterization of evolving populations by performing whole genome sequencing. Altogether, this interdisciplinary approach links genomic analysis and
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on five continents. The Czech Science Foundation funded PhD project will image the lithospheric structure of the Central Asian Orogenic Belt (CAOB) in the frame of the international project entitled
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and imaging methods or nuclear medicine At least 3 years of experience teaching in the field Doctorate (Ph.D.) in the field Excellent knowledge of Czech and English Prerequisites for scientific and
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Brno University of Technology, Central European Institute of Technology | Czech | about 2 months ago
The successful candidate will lead and contribute to research activities focused on nanoscale magnetism and spintronic materials, with a strong emphasis on advanced TEM-based magnetic imaging, data interpretation
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, including metabolomics, proteomics, metabolic cages, sequencing, and advanced imaging facilities · Scientific and strategic mentoring, including guidance in project management and individual consultations
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This research involves mouse studies (surgery and adoptive cell transfer), wet-lab techniques (cell culture, flow cytometry and imaging), and analysis of sequencing and spatial data. The candidate is expected
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to infectious stimuli. Candidate profile This research involves mouse protocols (adoptive cell transfers, infections), wet-lab techniques (cell culture, genetic editing, flow cytometry and imaging), and analysis
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imaging data. Building on recent critiques of overfitted prediction models, the project will implement a structured, multi-tiered analytical framework, comparing classical regression techniques with modern