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, extending them with physics-based approaches, and adapting existing physics-integrated neural network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell
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(including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A qualification that is highly valued in industry 30 days of annual leave and flexible working
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Infrastructure? No Offer Description Work group: IBG-4 - Bioinformatik Area of research: PHD Thesis Job description: Your Job: Develop methods and workflows to construct robust co-regulation networks from large
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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design
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trabajo - Nivel de ingles avanzado escrito y hablado. - Se valorarán estudios de postgrados relacionados con Sistemas Distribuidos -Degree in Software Engineering - Experience in network development and
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of American Universities. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/21881217/researcher-x2f-program-officer-membership-network-relations Return
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detection with minimal latency. Combined with efficient signal processing, this approach enhances detection accuracy while optimizing resource use, supporting cybersecurity and sustainability in IIoT networks
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methods for their bottlenecks, these steps will then be replaced or supplemented with ML-based surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs
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network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring the use of large language models to support neural network design and data preprocessing