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Field
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biology, molecular biology including mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required
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biomedical research field is emerging to address the ‘broken system’ of antibiotic R&D. It focuses on the actors and stakeholders seeking to develop a radically altered antimicrobial innovation ecosystem by
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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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dissemination skills. These capabilities are directly transferable to careers in cybersecurity R&D, secure hardware design, defence electronics, and post-quantum technology innovation, where demand for secure and
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, SAS, R, Stata, and relational database (e.g., SQL) tools Experience with statistical analysis in applications such as SPSS, SAS, R, and Stata using syntax/command files, macros in SPSS, SAS, and/or
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fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic
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information Further information may be obtained from Professor David R. Fuhrman (drfu@dtu.dk ). You can read more about DTU Construct at www.construct.dtu.dk . If you are applying from abroad, you may find
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on: Technical Expertise: Documented skills in Python, Matlab, R, and a strong working knowledge of UNIX environments. Proven familiarity with biological omics data analysis techniques is essential, along with any
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statistical analysis and/or coding (e.g., R, Python, C++) Exposure to neurophysiological measurement methods (e.g., eye-tracking, pupillometry) Interest or training in technology law, digital regulation, or AI
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research