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Documented ability to work in Python Experience with machine-learning methods for record linkage and text analysis Documented experience with machine-learning methods for image-to-text transcription
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. Application of Bayesian mixing models to investigate consumer diets and food web pathways Requirements To meet the general entry requirements you must have been awarded a second-cycle (Master’s) qualification
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chromatographic techniques. Integration and synthesis of previous data with newly collected data on fatty acids, cyanotoxins, and stable isotopes. Application of Bayesian mixing models to investigate consumer diets
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described. The project has three main objectives: (1) Use simulation models to make inferences on the role of sex ratio selection on sex chromosome evolution in a different meiotic drive scenarios, (2
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numerical modelling and programming as well as experimental work is a merit Experience from industry is a merit About the employment Fixed term position 48 months, in accordance with Chapter 5, Section 7
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and ability to communicate clearly Merits include: Knowledge of LLMs, deep learning, and Python programming Knowledge of power electronics Experience in modelling, simulation, and experimental work In
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Arabidopsis thaliana or a comparable model plant system. Very good written and oral English language skills. Meriting qualifications The following qualifications are not required at the point of appointment
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state-of-the-art genomic and epigenomic approaches to study chromatin dynamics in human cells and stem cell-derived neuronal models. The project will generate fundamental insights into the chromatin-based
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carries out research, undergraduate and postgraduate education within materials physics and materials chemistry. The division combines theory and modelling, materials synthesis, characterization, and
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researchers and doctoral students across 13 research groups. Research at LOE spans materials synthesis and chemistry, theory and modelling, fundamental materials physics, and device development, with