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-disciplinary involving algorithmics, stochastic optimization, multi-criteria decision making, and data science. As part of the project, you will implement and test algorithms and further develop your skills in
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nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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increasing environmental awareness. However, most existing hearing aid algorithms optimize for only one of these objectives at a time, often at the expense of the others. To enhance hearing aid performance
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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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of programming or scripting languages such as Python, Fortran, R or others. Experience in remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and
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strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
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analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of nonstationary models and algorithms for analyzing various