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Engineering of Catalysts for Hydrofunctionalization Reactions: From Selectivity Control to a Predictive Model” project financed from the funds of Priority 2 of the European Funds for a Modern Economy Program
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regulation of menopause, it captures key microstructural and mechanical consequences of tissue degradation relevant to menopausal fragility. This ex-vivo model will be validated against control and post
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks
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or intervention strategies are lacking, urging the need for new perspectives on pathogen control. Within this project these perspectives will be explored. To predict correlates of disease against these complex
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energy system models based on the institute`s own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE. Your tasks in detail: Implementing geothermal plants with material co-production in
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understanding of the underlying physical mechanisms and to leverage this knowledge to develop predictive tools for optimizing the design and control of wind farms. Research scope and responsibilities Depending
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; machine learning methods (i.e. supervised and unsupervised learning, deep learning, reinforcement learning, etc.); artificial intelligence methods (e.g., predictive modeling, natural language processing
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or predictive modelling, edge AI, AI for biomaterials formulation, processing and manufacturing optimization. Wearable devices – wearable physiological sensors, smart textiles, soft robotics, and exoskeletons
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understanding of ML approaches for classification, anomaly detection, and prediction using high-frequency data. Experience with multilevel longitudinal data, missing data strategies, and clinical outcome modeling
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, genomic selection modeling, bioinformatics, proficiency in R, Python and/or Linux command line • Experience with DNA/RNA extraction and library preparation • Experience working with large-scale datasets