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The Natural Language Processing Section at the Department of Computer Science invites applicants for a Postdoctoral Researcher in Natural Language Processing. Project Description The position
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collaboration with clinical colleagues at the hospital. The successful candidates will be joining a larger team of cross-disciplinary cancer researchers, with the aims to identify mutational processes and clonal
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-years of work experience) related to data science, bioinformatics, computer science or within natural sciences Excellent programming skills, preferably in Python and/or R Good software engineering
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, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process
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respectively. The positions are hosted by the IMAGE section at the Department of Computer Science, with research themes spanning computer simulation, robotics, biomedical imaging, computer vision, geometry and
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investigates the ecological and evolutionary processes that dictate the distribution, adaptation and impacts of weeds in agroecosystems. Our basic research uses weeds as excellent models for studying rapid plant
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/ Application procedure Your application must be submitted electronically by clicking ‘Apply now’ below. The application must include the following documents in PDF format: 1. Motivated letter of application (max
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: https://healthsciences.ku.dk/phd/guidelines/ Application procedure Your application must be submitted electronically by clicking ‘Apply now’ below. The application must include the following documents in
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, please contact Jens Petersen (phup@di.ku.dk ) or Raghavendra Selvan (raghav@di.ku.dk). Machine Learning for Design of Sustainable Food Processing Currently, plant ingredients are often refined to almost
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time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not considered. Doctoral Candidate requirement – the applicant must not be in possession of a doctoral