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– ISAS – e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and therapy of diseases like cardiovascular diseases
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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-cell genomics data, ideally using tools such as Seurat or Scanpy Enthusiasm for statistical modeling and machine learning to analyze complex biological datasets High level of care and attention to detail
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