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in healthy states, genetically perturbed states, and during liver regeneration. On the other hand, you will develop algorithms to disentangle direct intercellular signals from those that are induced
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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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University professorship (m/f/d) in 'AI in Occupational, Social and Preventive Medicine' (salary gra
implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare. Validation of models to ensure accuracy and reliability
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at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data, stochastic optimization
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
of this project requires the design, development, and training of an artificial intelligence algorithm capable of automatically segmenting the bony structures of both healthy and fractured tibial plateaus
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learning algorithms (e.g., graph neural network (GNN) architectures) will be developed to explain the identified small-scale processes as accurately and efficiently as possible and to ultimately develop a
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issues or areas of critical data examination. Works with statistics on defining and documenting programming endpoint algorithms across a study, drug program and/or contributing to TA level algorithms
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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
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or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. • An excellent
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. Interest in clinical algorithm development and dexterity with biostatistical coding in R or Python is a plus. The primary goal of this aspect of the CH CARE Study is to combine serially obtained somatic and