30 data-"https:"-"https:"-"https:"-"https:"-"MASSEY-UNIVERSITY" PhD positions at Utrecht University
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PhD Position on Parameterized and Fine-Grained Complexity of NP-Hard Problems Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40
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philosophical approaches; Learn to derive hypotheses from deductive theoretical reasoning through formal methods on sociological phenomena; Develop strong skills in experimental methods, data analysis and
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and/or educational projects. Within the Delta Values team, the PhD student will have their own clearly defined tasks, co-developed with the supervisory team. What will you do? collect and analyse data
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to accurately analyse and interpret research data and apply scientific literature. Strong communication skills in English, both spoken and written. This PhD position is part of an EU Doctoral Network, which
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investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for everyone. This ambition motivates our scientists in
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existing datasets and set up new studies, collecting samples from horses and performing laboratory experiments followed by data analysis. Techniques such as 16S rRNA sequencing, shotgun metagenomic
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3D printers, furnaces, centrifuges, and microfluidic devices. Meticulous data recording and analysis are essential, as the project combines practical engineering with fundamental physical chemistry
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quantitative data and qualitative fieldwork. Publishing research findings in peer-reviewed academic journals and presenting them at conferences. Collaborating with interdisciplinary researchers and engaging with
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-throughput phenotyping. You will develop novel methodologies, execute experiments, analyse data, and present your project results in the form of manuscripts and oral presentations. In addition to your research
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering