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as evidence of ongoing CIN. This PhD will work at the leading edge of single-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We
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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN
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well as fungal transformation is appreciated Experience with fluorescence microscopy Knowledge of programming, R, statistical analysis or bioinformatic is strongly appreciated Excellent English proficiency in
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, Medical Statistics and Informatics (EPICENTER), Medical University of Innsbruck Supervisor: Patrick Rockenschaub Start: as soon as possible (flexible) Duration: 3–4 years, fully funded In this ERC-funded
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-MEDIC (ERC Starting Grant) Host: Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics (EPICENTER), Medical University of Innsbruck Supervisor: Patrick
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administrative tasks, collaboration in evaluation procedures Your Profile Master degree or diploma in business administration/economics with a core area in banking and finance Excellent knowledge in statistics and
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in the management of projects (e.g. conferences) Good knowledge of MS Office (Word, PPT, Excel) and statistics programmes (SPSS, jamovi, R) knowledge of English Ability to work in a team with project
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, statistics or fluid dynamics Excellent knowledge of statistics Proven knowledge of Python, R, Matlab or a similar programming language Experience with Linux/UNIX environments Excellent oral and written
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development Outstanding knowledge of empirical social research methods Advanced competence in statistical methods and computer programs for analysis of quantitative and qualitative empirical data (e. g. SPSS
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, technical sciences, computer science or mathematics Experience in working with data analysis and statistics programmes Excellent knowledge of applied programming languages, such as Matlab Enthusiasm