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conduct world-class applied research. We change and make a difference. Do you want to become one of us? The PhD position is located within Department of Computer Science (DIDA) SDS (secure and distributed
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statistics This PhD project falls under the collaboration between Research Thrust RT2 Physics-based models, and Research Thrust RT3 on representation, compression, learning, and inference. For long-distance
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20th April 2026 Languages English English English Interested in how starter cultures enhance food safety and reduce waste in modern food production PhD scholarship within Food Microbiology Apply
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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM
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this industrial PhD studentship in Physics – fully funded by the EPSRC and QinetiQ. We’re looking for a student who has a passion for science, with ambition to learn and apply their own ideas, perspectives, and
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/Associate Professor, you will: Teach and (co-)develop Bachelor and Master level courses within the SISSTEM programs, working closely with other lecturers and (PhD) researchers. Supervise and coach student
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 5 hours ago
for this position, please navigate to the UT Health Careers portal at: https://wp.uthscsa.edu/careers and enter keyword 26000044. Visit our website to learn more about UT Health San Antonio and the excellent
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of photovoltaic solar potential Duration: 3 months Maximum Duration Including Renewals: 3 months Monthly Maintenance Allowance: €1,851.00 Where to apply Website https://fenix.tecnico.ulisboa.pt/fenixedu-admissions
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network structures. Methods from graph theory, machine learning, and artificial intelligence will be employed to model complex relational structures and identify patterns in high-dimensional data. The work