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Field
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Develop new machine learning
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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check our website for more information: https://www.uni-goettingen.de/de/635183.html PhD students with their own funding (e.g. DAAD) can join at any time. Tuition fees per semester in EUR None Combined
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/ ). By combining advanced machine learning techniques with qualitative methods, the project will investigate usage patterns and engagement levels with a health app across multiple European countries
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data integration data quality data analytics programming languages (SQL, Python, Java) Complementary IT skills: machine learning image recognition sensor technologies robotic technologies
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Dynamics, Bioprocess engineering, Data Science, Machine Learning, Computational Chemistry Offer Description MSCA Doctoral Network machinE LEarning for inteGrated and multi-parAmetric eNzyme and bioproCess
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applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language skills. Experience with
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You