90 parallel-computing-numerical-methods positions at University of Southern Denmark in Denmark
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courses—preferably at the master's level. You should be familiar with the methods and tools used in the courses Data Driven Decision Making (DS810) and Applied Machine Learning (DS807), including practical
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their academic profile in LSP will be to work on so-called “zero programming” methods and tools to define a digital workflow from product design to production operations. Based on analyzing digital product
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secondary school education) funded under the Interreg 6A program. The interreg project primarily aims to develop and implement pilot projects, thereby contributing to measure: a) Development and
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cognitive, biological, and experimental psychology as well as methods and supervision of bachelor’s and master’s theses. One position will have main employment and teaching responsibilities at Campus Odense
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this project, the candidate will develop new computational strategies to identify human genetic variation linked to cell fate changes in neurodevelopmental disorders and cancer. The candidate can use and combine
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University of Southern Denmark, IMADA - Department of Mathematics and Computer Science Position ID: SDU -ASSISTPROF1 [#26735, 3023] Position Title: Position Type: Non tenure-track faculty Position
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, stimulation and transduction of T cells, and standard molecular biology methods, including cloning. Experience with flow cytometry and animal work is essential. Hands-on experience using cancer models in mice
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asset. Familiarity with quantitative text analysis procedures is considered an advantage. Familiarity with digital tools, including computational methods for textual analysis, will be an advantage
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preparation and characterization of lipid nanoparticles Experiences with spectroscopic methods UV/VIS and fluorescence techniques The applicant must have an undergraduate and graduate training in Chemistry
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these intricate immunological processes. Using advanced bioengineering methods and innovative molecular tools, this project aims to: Develop robust 3D skin-on-a-chip models incorporating genetically engineered