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sciences in carrying out concrete AI projects. This includes compiling, organizing, and sharing key datasets, assisting with resource allocation proposals, conducting machine learning workflows, and
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sciences, and create partnerships with industry, healthcare and other national and international actors. We are now looking for an outstanding candidate with expertise in machine learning, bioinformatics
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at the intersection of numerical analysis and scientific machine learning, focusing on the development of reliable, physics-aware AI frameworks. The aim is to build a mathematically grounded approach for approximating
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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performance in organic electronic and electrochemical devices. Multiscale simulation and integration of machine learning: Use molecular dynamics, quantum mechanical and continuum models, in combination with
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focuses on the creation of visual representations that create insights and clarification of complex data. This includes the interpretability and explainability of machine learning models
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artificial intelligence (AI)/Machine Learning (ML) with a focus on life science, or alternatively, life science with a focus on AI/ML (or equivalent). You will work closely with researchers, engineers, and
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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on how your research can be further developed into innovations. You are interested in driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize
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in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about