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of a Master's degree in Computer Engineering or a related field and enrolled in a PhD programme in Computer Engineering or a related field. [registration is not mandatory during the application phase
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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research focusing on the project topics described above. Manage large datasets. Perform statistical analysis and econometric analysis of the data using appropriate software (Stata, R). Carry out and develop
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oversee and coordinate the work of junior staff and students on data curation, analysis, and pipeline-related tasks, ensuring adherence to established workflows and quality standards. QUALIFICATIONS PhD in
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field data and controlled experiments. Insights from the project will have practical applications in pest control and livestock management. The candidate will be encouraged to develop, simulate and
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fitness and tumor initiation. We welcome applications from recent PhD graduates who have published their thesis research and who are interested in this research area, particularly those who may have prior
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: Master’s degree (120 ECTS credits) or equivalent qualifications in ecology or related areas when starting the PhD position. You have a solid methodological foundation in ecological data collection and
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. Possessing a Master's or PhD degree will be advantageous Experience and Knowledge of operating HPLC, MALDI-TOF and Q-TOF Mass spectrometry for protein sequencing, carbohydrate/Sugar analysis, and polyphenol
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(EHR) data, large data sets, or geospatial analysis. A record of submitting external funding applications (e.g., F31, T32, foundation grants). Background Investigation Statement: Prior to hiring
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across commercial, residential, transportation, and occupational settings · Collect and synthesize environmental data, contextual observations, and metadata · Perform statistical and qualitative analysis