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management, BOKU University, Peter-Jordan-Straße 70, 1190 Vienna; E-Mail: [email protected] . (Reference code: 144) We regret that we cannot reimburse applicants travel and lodging expenses incurred as
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relation to multilingualism and memory) Background in biomedical engineering Experience in advanced analysis of brain functional and structural data Coding skills (Python, MATLAB, R, Linux/Bash) Very good
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, conference presentations) A statement from your supervisor committing to support your finalization phase Compliance with the CoBeNe regulations for PhD candidates (agreement to the Code of Good Practice, FÖP
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Coding skills (Python, MATLAB, R, Linux/Bash) Very good English and German skills (B1) Team player with strong social / communication skills Coding skills (SPSS, JASP, R) Very good English and German
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developed within the group, turning research ideas into working and reliable code; design and run experimental evaluations for the group's research projects; support group members with the technical side
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models developed within the group, turning research ideas into working and reliable code; design and run experimental evaluations for the group's research projects; support group members with the technical
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University of Natural Resources and Life Sciences, Vienna (BOKU) | Austria, | Austria | about 2 months ago
the reference code 149 to [email protected] until 1st of September 2026. If you are invited to a personal interview, travel expenses can be reimbursed on presentation of invoices and proof of payment (in
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. This includes version control and release management, code quality and maintenance, bug fixing, testing and quality assurance, documentation, as well as support and training. You will work closely with another
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WienCountryAustriaCityViennaGeofield Contact City Vienna Street Karlsplatz 13/ 249-01 Postal Code 1040 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone
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further developing these modules, i.e. providing, maintaining and documenting Python and R code for further use in AMDC projects, using modern data science methods and machine learning approaches