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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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healing, and nuclear mechanosensing. The successful candidate will have established experience in the following areas: (a) imaging techniques such as fluorescence, confocal, and multi-photon microscopy, (b
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proficiency level, nationality, visa requirements, date of birth, experience overview, and publication list. Contact information for at least three academic references. A support letter will be requested by us
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in English in one PDF file. The file must include: Application (cover letter) Full CV Academic Diplomas (MSc & PhD – in English) List of publications incl. link to Google Scholar profile Link to Github
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certificates/PhD diploma, etc.) Complete list of publications indicating the publications attached Applicants may choose a maximum of two publications for assessment. Please attach one pdf-file for each
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file. The file must include: Application (cover letter) CV including date of birth, employment history, H-Index, citations and ORCID Academic Diplomas (MSc/PhD – in English) List of publications
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of birth, employment history, H-Index, citations and ORCID Academic Diplomas (MSc/PhD – in English) List of publications indicating scientific highlights One-page summary of your PhD thesis FELASA
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. The file must include: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Applications received after the deadline will not be considered. All interested candidates
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and