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knowledge of process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
transcriptomics. The main projects are the analysis of gene expression patterns in malignant human tumor samples mostly coming from clinical trials and preclinical model systems, and on the continued development
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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robust descriptors (e.g., water activity, sorption, glass transition temperature, plasticization, porosity, internal distribution) and provide predictive guidelines to rationally select and design drying
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data
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on the project can be found here: https://hecustom.eu/ This post will contribute to the creation and validation of a digital twin (with biological bone models) to assess and interrogate the issue of
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Details A brain decoding model aims at predicting what sensory stimulus is received (e.g. visual stimuli, different images), which mental state is experienced (i.e. asleep, awake, drowsy) or even what is
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. The successful candidate will contribute to the development of predictive numerical models and experimentally validated designs for intricate mechanical assemblies, deployable structures, compliant mechanisms, and
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model predictions with biological knowledge and external data sources. Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological
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of large, cross-departmental initiatives. The analyst deploys data extraction, transformation, and loading (ETL) processes; classical statistical analysis; predictive and prescriptive modeling; optimization