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physics and cosmology. The research areas of interest include (but not limited to) the following fields(*1,*2): 1) Physics beyond the Standard Model and Cosmology axion physics, dark matter, flavor and CP
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on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from various sources, such as
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and dexterity. Ability to work independently, as well as a team member. Prior experience with zebrafish or model organisms is a plus. Additional Information Appointment End Date: this is a one year term
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MATCH Doctoral Network, a Marie Skłodowska-Curie Actions (MSCA) project funded by the European Union, is currently recruiting highly motivated candidates for fully funded PhD positions across top
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summative evaluation plans and construct comprehensive logic models that capture program activities and outcomes. · Design evaluation procedures/protocols and develop data collection/survey
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contribute to the design and development of Machine Vision approaches for the quantitative analysis and phenotyping of agricultural systems: Training/Development of computational models for the quantitative
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of preclinical models. Collaborate with other projects of the group, by promoting fruitful discussions or by helping in experimental work Participate in general activities of the group Support the principal
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models of society and their resilience. Since 2019, SCRIPTS has been funded by the German Research Foundation (DFG) under Germany’s Excellence Strategy (Exzellenzstrategie) initiated by the federal and
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modeling, environmental simulations, and digital twin systems. -Develop analytical tools, visualization platforms, and decision-support dashboards to improve research outcomes. -Ensure data quality through
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well as emerging materials. These experimental techniques will be complemented by advanced electromagnetic modelling. Responsibilities and qualifications The ideal candidate will possess demonstrated expertise in