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to environmental stress. The successful candidate will work at the interface of molecular biology, physiology, and omics technologies to dissect regulatory networks in model and/or crop plants. Key Responsibilities
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values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker
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city models focused on health and environmental infrastructures. Advanced Data Analysis: Advanced skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban
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Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly
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skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Chemical engineering or a related field. Extensive experience in unit operations and chemical processes. Ability to design and
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materials and production methods for prosthetic devices. Design and execute experiments to optimize the manufacturing process. Collaborate with multidisciplinary teams to integrate technological advancements
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to dissect regulatory networks in model and/or crop plants. Key Responsibilities Design and execute experiments to study molecular and physiological processes in plants. Utilize tools such as proteomics, and
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excellence in the domain of renewable energy-powered water harvesting systems. Design and model advanced systems based on condensation, sorption, or hybrid thermal processes using solar and alternative energy
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performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing, comminution modeling, and ore characterization, and will contribute to developing
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to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its research