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We are seeking a highly motivated candidate who has recently completed, or is close to completing, a PhD and has training in statistics, data processing, bioinformatics, or a related discipline, to
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dissolution behaviour Analyse time-resolved experimental data using statistical and machine-learning approaches, and validate predictive models using independent experiments Design and conduct controlled
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, physicochemical and functional properties, process, analyse and interpret experimental data using appropriate statistical methods, contribute to scientific publications, project reports, presentations and other
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of molecular, spatial, histopathological, and clinical data. Computational and statistical analyses will be performed primarily using R. The research is carried out in a multidisciplinary environment and in
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that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the date of the employment decision. Under special
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statistical analyses will be performed primarily using R. The research is carried out in a multidisciplinary environment and in collaboration with clinical researchers and other relevant partners. Work duties
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privacy for data to be used for machine and statistical learning. It is well known that data can be highly sensitive, and that naive anonymization is not sufficient to avoid disclosure. Models and
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deficiency but potentially also PSC and MASLD), exploring risk factors and prognosis of diseases where histopathology is essential. The position requires a high level of statistical/mathematical competence
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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skills in experimental design, laboratory and field research on animals, statistical modelling and programming, evidence synthesis, climate modelling, open and reproducible research, scientific writing