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Field
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 days ago
manufacturing and structural analysis by simulation in the testing pyramid for certification of aeronautical structures, increasing the reliance on digital technologies (data or simulation driven) to ensure
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, with emphasis on robustness, generalization, and performance in high-dimensional and noisy biological datasets. See this publication for additional details: https://doi.org/10.1111/ede.12449 . The second
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 4 days ago
network and determine the biological tumour properties responsible for this signature. Subsequently, based on these findings, the role of the electrophysiological context in GBM biological properties
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processes. Projects can include assembling, sharing, integrating, and advanced analysis of large amounts of data from diverse sources, including experiments, observations, and simulations, to gain a deeper
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policy and long-term care for older adults, including those living with dementia. Participate in clinical research in the nursing home setting. Contribute to data analysis, manuscript preparation, and
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• Computational skills for multi-omic data analysis (R, Python) is a plus. Department Contact for Questions Dr. Asmaa El-Kenawi Email: asmaa.elkenawi@cancerimmunometabolism.com Website: https
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD project focuses on security analysis of critical infrastructures with an emphasis on communication
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international and multicultural environments; - Experience in organizing events; - Experience in managing social networks and newsletter; - Experience in laboratory work; - Experience or volunteering in
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https