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MB per file. In case you have more than one file per field you need to combine the pdf-files into a single file, as each field handles only one file. We do not accept zip-files, jpg or other image
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collaborative and social abilities. Prior experience with metabolomics, transcriptomics, bioinformatics, and imaging is a plus. For more information, please feel free to contact Per Svenningsen at psvenningsen
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learning research. You have prior experience developing ML models for image processing and segmentation tasks You have experience in developing data pipelines for processing satellite imagery You study in a
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information from medical images, improvement of image quality to support dose calculation and adaptive treatment delivery, and statistical modeling of patient data as well as development of efficient methods
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energy-efficient CMOS blocks implementing SSM-based LLMs. Prototype hardware blocks on FPGA and prepare for ASIC tape-out. Benchmark performance and comparison with transformer accelerators. Work with
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facilities in imaging, immunology, tissue engineering, and bioinformatics. Qualifications We seek applicants with the following qualifications: Essential: PhD in molecular biology, immunology, biochemistry
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of flora and fauna, ecosystems ecology, environmental sociology, stakeholder engagement and integration, R-coding, GIS, and mapping software will be beneficial. More specifically, we welcome a candidate with
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Mass Spectrometry and Systems Biology research unit’ at BMB and the ‘Danish National Mass Spectrometry Platform for Proteomics and Biomolecular Imaging’ (PLATO), which provides a highly international
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the pdf-files into a single file, as each field handles only one file. We do not accept zip-files, jpg or other image files. All pdf-files must be unlocked and allow binding and may not be password
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and aim to develop a long-term research plan based on the clinical functions of the department. A particular focus will be on prostate cancer, including areas such as early detection, screening, imaging