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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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genetics to predict breast cancer risk and tumour aggressiveness in BRCA variant carriers Digital biomarkers for enhanced AI-guided therapy in heart failure (D-BEAT) Experimental models for optimizing
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to new ideas and hypothesis An active and international PhD program Possibility to discuss ideas with experts in the group for secondary metabolite analysis, molecular genetics and Trichoderma species
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of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user skills, including MS Office and other programs e.g
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-haves: Completed Master's/Diploma degree in the field of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user
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aspects of archaeological science, proteomics, genetics and dating; Writing and preparing scientific reports and journal articles and present conference papers and posters; Representing the group