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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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analysis across case study regions. The successful candidate will work on the development and application of AI/Machine learning and behavioural modelling within the North and Baltic seas, utilising legacy
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talented Machine Learning Engineer with expertise in healthcare data analysis, medical terminology, and cutting-edge machine learning techniques. The ideal candidate will play a crucial role in designing
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Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology by: Developing
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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16.01.2026 – 2:00 PM – Resolution of appeals 16.01.2026 – 4:00 PM – Final results Additional comments We are seeking a PhD student in Machine Learning for EO Image Processing to join our team, who will be
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
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Robust machine learning using information theoretic approaches for damage detection in complex machines (C3.5-ELE-Esnaola) School of Electrical and Electronic Engineering PhD Research Project