136 programming-"https:"-"https:"-"https:"-"C.N.R" Postdoctoral positions at Nature Careers
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: Experience specifically designed programs to enhance professional growth and career readiness empowering postdocs for success beyond their training. This includes access to grant writing workshops, individual
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. Please find more information about entering and working in Denmark here . Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can
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Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in
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, (desired) WE OFFER: Salary according to tariff agreement, extra annual payment, and company pension plan (VBL) 30 days of vacation per year, plus two additional days off on Christmas Eve and New Year's Eve A
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, bioinformatics, biomedical sciences, biostatistics, or a related discipline. Expertise in human genomic and transcriptomic studies and a strong interest in neurodegenerative disorders. Programming
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aims to achieve reliable genome design and synthesis – engineering cells to have specific functions – which will be a major milestone in modern biology. A dedicated social science program will support
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. Please find more information about entering and working in Denmark here . Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can
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of the following methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning
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novel machine-learning methodologies Excellent programming skills in Python and familiarity with modern ML tooling and reproducible research practices Experience training and deploying machine-learning