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software modules, protocols, or frameworks that use NIST-standardized PQC algorithms Evaluate performance, interoperability, and security implications of replacing classical cryptographic schemes with
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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science Designing, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing reports, scientific papers, and presentations Project duration: 6
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architectures to identify upgrade paths for quantum-safe migration Design, implement, and test software modules, protocols, or frameworks that use NIST-standardized PQC algorithms Evaluate performance
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably bachelor's degree in Computer Engineering, Computer
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surfaces (RIS) and associated signal processing for terahertz communication links. The project aims to develop advanced RIS, corresponding channel models, and efficient signal processing algorithms
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application, developing groundbreaking algorithms and systems that mimic natural processes to elevate the capabilities of robotic systems. In this role, you will engage in transformative projects that utilize
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application, developing groundbreaking algorithms and systems that mimic natural processes to elevate the capabilities of robotic systems. In this role, you will engage in transformative projects that utilize
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, developing groundbreaking algorithms and systems that mimic natural processes to elevate the capabilities of robotic systems. In this role, you will engage in transformative projects that utilize bio-inspired
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for TBM risk identification Developing practical tools to optimize TBM operation parameters Writing