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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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executing data collection and analysis for multiple research projects, with special attention to Youth Justice projects. Candidate must have a degree – preferably a master’s degree, PhD, or PhD candidate
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discipline Solid wet-lab experience in molecular biology, ideally with tissue or protein work Motivation to develop bioinformatics and data analysis skills (training provided) Proficiency in English (spoken
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: The successful candidate will work primarily on the following sections of the project. Data analysis: In conjunction with Dr. Deborah Maia de Lima and Dr. Claudia Mitchell, the candidate will : 1) Transcribe and
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executing data collection and analysis for multiple research projects, with special attention to Crisis Response projects. Candidate must have a degree – preferably a master’s degree, PhD, or PhD candidate
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conducting human studies with human participants including participant recruitment, data collection, and management of data Advanced skills in statistical analysis using software such as R, STATA, or SPSS
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Max Planck Institute for Plant Breeding Research, Köln | Koln, Nordrhein Westfalen | Germany | 14 days ago
, maintenance and troubleshooting on an Aria Fusion cell sorter Sample preparation, cell sorting and data analysis Generation of single cell libraries with 10X Genomics, Singleron and BD Rhap-sody platforms
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population-based studies. Using data from 11 million vessel segments from over 200,000 CFPs, we have shown that retinal vasculometry can predict cardiovascular disease as well as established risk scores and