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efficient decoding algorithms" supported by the Luxembourg National Research Fund (FNR). The APSIA Group is seeking a highly qualified post-doctoral researcher for this project. For further information, you
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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academic and professional qualifications Proven research experience in the field of modelling and analysis of biological networks Solid foundation in mathematics and algorithmic design Strong programming
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classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high-throughput, automated analysis of large image datasets from fluorescence
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neurophysiological biomarkers with long-term neural activity recording and artificial intelligence algorithms to for conditions such as pain, Parkinson’s disease, sleep disorders, Alzheimer’s disease (AD), and
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health and disease, and experience in the algorithms used to analyze these datasets. The appointee will ultimately create an independent research effort with dedicated extramural funding that complements
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Student or Postdoc (f/m/x) for the project Theory and Algorithms for Structure Determination from Single Molecule X‑Ray Scattering Images Project description Single molecule X‑ray scattering experiments
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern