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experimental molecular biology laboratory. We believe that AI and Machine/Deep learning can be complemented with statistical and mathematical modelling to arrive at a systems level description and understanding
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at least 7 years of hands-on work experience in LC- MS analyses of preferably organic contaminants in a routine or research environment, like pharma or food; preferably has affinity with statistics and data
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in Biology, Plant Sciences or a related discipline; proven interest in insect ecology and biological pest control; experience with experimental research on insects; experience with statistical data
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understand how forest fires and climate change interact on a global scale. You are available from September 2024 onwards, or sooner. You also possess: At least intermediate statistical and mathematical skills
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of fresh produce and shellfish. In the projects we use process-based and statistical models to evaluate these impacts. In this role you will be responsible for data gathering for the models, developing
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/consumer behavior; statistical/ modelling skills and experience with quantitative data collection (survey research, lab and natural experimental research are parts of this project); an interest in conducting
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science, marketing, social psychology, behavioral economics). Other backgrounds will not be considered; statistical/ modelling skills and experience with quantitative data collection. Surveys, and (lab and
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conduct research into measuring and further analyzing (statistical methods) choice and eating behavior, (multi)sensory perception, consumer preferences, etc.; you contribute to project proposals
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(such as neural networks and deep learning) to address systems biology problems and a deep understanding of mathematical and statistical modelling of biological systems. In addition, you have strong affinity
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, R or C); proven knowledge and skills regarding research design, quantitative, qualitative and/or spatial-temporal methods for data collection, and quantitative (statistical) and/or qualitative