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umbrella organization and builds on four pillars: Qualitative methods; Experimental methods; Computational Social Science, as well as Skill School (https://www.sam.lu.se/en/research/lund-social-science
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Description of the workplace At the Division of Engineering Geology (tg.lth.se) , we work with education and research focused on methods for assessing properties of geological materials, minerals
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science, neuroscience, statistics, physics, mathematics or a related discipline. Competence using Linux-based high-performance parallel computing systems. Familiarity with git and GitHub. Experience building pipelines
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independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout
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undergraduate education, not least in the Master's programme "Engineering Nanoscience" at LTH. Being a doctoral student As a doctoral student, you are both admitted as a student and employed at Lund University
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completed postdoc on a topic relevant for this position. Documented general and specialised knowledge of computational and modelling methods. Documented ability to apply for and obtain external research
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' at the Faculty of Science, 'Algebra, Analysis, and Dynamical Systems,' 'Applied Mathematics,' and 'Computer Vision and Machine Learning' at the Faculty of Engineering, as well as Mathematical
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computing. The LunDMX group currently consists of a senior researcher, three faculty members, a postdoc, an engineer, and two Ph.D. students. Project description The overarching theme of this project is to
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. The WISE Fellow will participate in collaborations, education, and activities of the WISE programme. The associate professor position is a six year tenure track position, where the first four years
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including funding for two PhD students and two postdoctoral researchers. WISE Fellows will engage in collaboration, training, and activities within the WISE program both nationally and at Lund University