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Developing advanced computational imaging algorithms Proof-of-principle experiments on complex nanomaterials and biological samples We are looking for candidates with a completed university degree in physics
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-throughput experiments in molecular biology, image and video analyses as well as pattern recognition of complex public health data Collaboration in the development of algorithms/methods and development
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silico approaches. This may include mathematical modeling of biological systems, machine learning and artificial intelligence methods, and the development of innovative algorithms and software pipelines
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Contribute to the development of new algorithms and methods for the efficient analysis of large-scale omics datasets Participate in workflow automation and management using systems such as Snakemake
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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intelligence (AI) has the potential to substantially improve medical care, from early diagnosis to treatment planning and follow-up. Despite rapid technical advances, many AI algorithms in healthcare do not yet
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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robotics Goal-driven agentic AI Autonomous medical imaging Design of AI-enhanced medical devices Machine learning models and algorithms for medical signal processing Embedded AI Privacy-aware AI Foundations
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications