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Field
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-modal datasets. It will use advanced analytical models to generate evidence about new and existing inflammatory pathways and how these will impact the progression of dementia. The PhD (DPhil) programme
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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(BIGS Mathematics) Teaching language English Languages Courses are held in English only. The thesis can be written either in German or English. Full-time / part-time full-time Programme duration 6
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Award (IDLA). This research aims to investigate natural source zone depletion (NSZD) processes that can naturally remedy oil pollution and use this improved process understanding to enhance CoronaScreen
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview As a Quantitative Research Intern at Susquehanna, you will work
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, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview As a Quantitative Systematic Trading Intern at Susquehanna, you will work
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performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior Alpha Monetization. Blend quantitative
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“Bioactives – Analysis and Application”. As part of this prestigious Alliance PhD program, you will collaborate closely with Queensland University in Australia and the University of Copenhagen in Denmark
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imaging. Strong analytical skills and experience with medical imaging technologies and data analysis. The ability to work collaboratively in multidisciplinary teams and communicate effectively across