119 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" scholarships in Belgium
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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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industrial Ph.D. position focused on developing scalable, Machine Learning (ML) pipelines for genomic and epigenomic biomarker discovery from Oxford Nanopore Technologies (ONT) long-read sequencing data
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position on GW data analysis using machine learning (ML) with expected starting date February 2026. The position focuses on using neural posterior estimation for tackling issues related to the analysis
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of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of in-air acoustic sensing and applied machine learning for building the next-generation of intelligent robotic
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experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit; The qualities to carry out independent research, demonstrated e.g., by the grades obtained in your (under
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motivated to learn. Comfortable working at the clinic–lab interface; excellent writing and communication in English (Dutch is an asset for patient-facing coordination). Motivated to work within an
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. Machine learning will assist in artifact correction, segmentation, and material classification. By combining experimental imaging, simulation, and data-driven interpretation, this approach will deliver high
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to learn are essential. Solid programming skills in Python and/or R; experience with reproducible workflows (Git, Snakemake/Nextflow, containers) is a plus. Interest in cancer biology, tumor microenvironment
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. dr. Erwin Dreesen, mail: erwin.dreesen@kuleuven.be Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60606922?hl=en Requirements Research FieldPharmacological sciencesEducation
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that monitors the radiation beam in real time, learns from data how the dose evolves, and autonomously reacts to protect patients from anomalies. The work involves both experimental physics and AI modelling