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as a workplace National Bioinformatics Infrastructure Sweden (NBIS) is recruiting a bioinformatics expert to the national support team for electron microscope image analysis and multimodal 3D data
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this fellowship can be obtained from Ylva Engström: Phone +46-(0)8-164166, Email: [email protected] Application Applications should be marked with reference number SU-465-0125-26 and submitted electronically as a
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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview. We welcome your application no later
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the date above will not be considered. Please attach your selected research publications electronically, in pdf or word format, in the application template. Research publications, e.g. monographs, which
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of special relevance Copy of the PhD, master’s degree (or equivalent) and course grades and other merits Short description (max 300 words) of your doctoral thesis If available, an electronic version of your
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monitoring of health. The precision medicine research is expected to make use of existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging, electronic health care records
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contact details of at least 2 reference persons. Doctoral position 4 years, starting according to agreement. The application is made electronically (via the system Varbi). For more details on the research