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Field
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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the collection, processing, and analysis of physiological data from recreational and elite athletes across various exercise protocols. Utilizing machine learning and deep learning algorithms, integrate multi-modal
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(and other geophysical techniques) forward and inversion modeling. Write professional-level codes/algorithms. Publish quality research results in peer-reviewed publications and presentations. Participate
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not limited to using UAV platforms to characterize active fire thermal and gas emissions, improve spreading models and detection algorithms, and assessing post-fire effects. The aim of the project is to
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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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. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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. Experimentation & Implementation - Develop and implement the related algorithms, models, and techniques. - Perform rigorous benchmarking and evaluation of the developed models. - Optimize algorithms for efficiency
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Engineering or equivalent from a recognized University. Major in Power Engineering will be advantageous. Minimum 5 years of relevant experience in power electronics, drives, control algorithms, optimization
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interest in methods development Experience in one or more of the following areas: algorithms development, transcriptome analysis, RNA modifications, statistics, machine learning, long read RNA-Sequencing
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with