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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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be adapted to mechanical sensors in the quantum regime for various applications. Your role The experimental work in all these projects involves design of the samples and of the measurement setups
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mechanisms that drive them toward tumorigenesis. By identifying common epigenetic pathways across different cellular contexts, we aspire to pinpoint actionable targets suitable for therapeutic intervention
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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models. Review and validate different approaches and existing models. Publish research findings in scientific journals and present them at major medical/scientific meetings. Must Have: A Ph.D. degree in a
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computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET
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underwater frames and instrumentation, including sensor testing and calibration Quantifying benthic biogeochemical fluxes and momentum fluxes in situ from high-density datasets (e.g. using eddy covariance
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are for different levels of decision-making. The position is for two years and will commence April 1, 2026, or soon thereafter. The position is within the research section Management and Modelling (MAMO
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the application of GC- and LC-MS/MS based methods for the analysis of these carcinogenic pollutants/metabolites from different chemical classes in hair, blood and urine samples. The study will also involve
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algorithms, NLP models, and LLMs to analyze complex data. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and