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background in grid-connected power converters. · Deep knowledge of advanced power conversion topologies, particularly MMC and SST. · Proficient in simulation tools for power converters, such as
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language processing), machine learning, or data science. Preferred Qualifications Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3
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patients with the genetic disease hereditary hemorrhagic telangiectasia. Approaches make use of spatial omics, advanced imaging techniques such as 3D deep tissue staining, microCT, and synchrotron imaging
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combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a
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weekly working time of 40 hours per week. The position can be filled on a part-time basis. Background: Addressing climate change and biodiversity loss requires a deep understanding of global land-use
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa
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foundation and programming skills in languages such as Python, Java, Julia, MATLAB, R, and/or C++. Expertise in one or more of the following: machine learning, deep learning, HPC, Docker/Singularity
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communication and collaborative skills. Experience with SLAM, sensor fusion, LiDAR/depth camera data processing. Familiarity with deep learning for obstacle avoidance (e.g., map-less navigation). Background in
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Postdoc in Machine Learning for Oligopeptide Design (1.0 FTE) (V24.0584) « Back to the overview Job description The advent of modern machine learning (ML) methodology is accelerating scientific