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Field
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surface temperature) with eddy flux measurements to scale up findings and develop predictive models of water use efficiency, and c) quantify water use efficiency and its temporal and spatial variability
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initial contract of two years Background The post-doctoral researcher/university researcher will be working on the EU’s Destination Earth Climate Change Adaptation Digital Twin Project, Phase 3 (https
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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; • Integration of Genomic Prediction and Crop Growth Models; • Genomic prediction & GWAS optimization; • Publication of scholarly works; • Occasional grant writing; • Occasional graduate student mentoring
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characterization, and computational modeling. Prior experience with solid-state NMR spectroscopy, including magic-angle spinning experiments, multinuclear NMR, quadrupolar nuclei, or two-dimensional NMR methods, is
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aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as well as machine
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data integration, image segmentation, predictive modeling, and uncertainty-aware active learning approaches. Perform data analysis and collaborate on physics-based simulations to support closed-loop
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Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong
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an intense of microbial activity contributes into the process of stabilization of organic matter; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict
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models using simulation and experimental data to predict material properties and guide further study. Document datasets, benchmark performance, and interpret results for validation and follow-up analysis