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. Responsibilities Model Development: Build and train advanced deep learning architectures (e.g., CNNs, Transformers, Generative Models) to decode the regulatory logic of genomic enhancers in GBM
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software. Knowledge of explainable AI methodologies. Experience integrating heterogeneous instrumentation under unified control architectures. Track record of publications in high-impact journals in
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requirements should be implemented; design and propose architecture and operations concepts and propose recommendations on the most promising technologies that should be leveraged; prototype software
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). The team focuses on the development and design of reliable, safe, and secure software systems, carrying out both upstream activities such as requirements quality assurance and architecture analysis, as
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based architecture with 2D-connectivity Migration to industrially fabricated devices Your Profile: Master and PhD in physics or a related field In-depth experience with quantum control experiments
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benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Human Genetics and the following skills: Strong interest in the field of genetics, neurobiology and psychiatry. Computer skills: strong level in
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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an expanded coherent and exascale-ready software stack featuring breakthrough research advances that meets the needs of complex parallel applications and the requirements of heterogeneous exascale architectures
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data for European and international funding applications. Specific Requirements PhD in Physics, Engineering, Mathematics, Computing, Bioinformatics or related fields. Master's degree in Data Science
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architectures to solve data-driven sensing and control problems related to turbulent atmospheric flows. The work will center around investigation of reinforcement learning and convolutional neural networks