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an experimental team, with direct availability of experimental validation for machine learning models. Competitive salary and full benefits. Access to state-of-the-art computing infrastructure. Fully funded for 4
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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programming models and high-performance computing techniques and machine learning models. Practical experience in the programming of high-performance computing of AI and/or scientific computing applications
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affected by warping, addressing both audio analysis and synthesis tasks. The methodological scope spans stochastic signal processing and machine learning, including hybrid physics‑guided and data‑driven
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machine learning approaches to link gene-regulatory programs to neuronal phenotypes. Use explainable sequence-to-function models to interpret regulatory logic underlying neuronal identity and function
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems
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safety. In particular, the candidate will investigate and further develop statistical and machine learning methods for modelling and forecasting traffic safety outcomes, and contribute to data collection
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at the interface of machine learning, deep learning, geospatial AI, causal modelling, and digital health systems. Your Role You will develop the core AI and data-driven models that transform large-scale
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machine learning (ML) models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and configurations
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, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining optical system design, signal processing, machine learning, and