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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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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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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow
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attacks Develop and implement ML algorithms to identify vulnerabilities and predict potential threats in supply chain systems Prepare project deliverables and disseminate results through high-quality
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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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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