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research profile to further integrating wet-lab techniques (such as single-cell sequencing, -omics) with advanced data analysis, for example through bioinformatics, machine learning, or AI. Themes such as
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-cell transcriptomics, or spatial tissue profiling data, and are keen to develop new methods, for example using machine learning. You have a proven track record of independent research funding and high
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). Experience applying statistics and Machine/Deep Learning to real-world data. Experience working with manufacturing process data, robotics systems and/or metrology data (sensor data, quality data, measurement
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language processing, and more. We own and operate the entire technology stack for Machine Learning Operations. This ensures that the models we build translate into secure, reliable, and actionable outcomes across
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27 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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multimodal data integration across organismal domains and data modalities, making use of state-of-the-art methodologies such as systems/network analysis, artificial intelligence and machine learning and/or
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to develop new methods, for example using machine learning. have a proven track record of independent research funding and high quality publications. have at least 5 years of post-PhD work experience
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cases. We are particularly interested in how AI, Data Science, or Machine Learning techniques can be used to quantify and assess software and system security from open source software to cloud services
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and machine-learning-driven analyses create opportunities for high-frequency, minimally invasive measurements. Proof of concept will be used in sheep, cattle or pigs, initially based on data from
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and scientific activities to building (international) community efforts around data science and machine learning. As Science Operations System Engineer for Cloud Platform development, you will be tasked