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Assistant Professor in artificial intelligence (AI) with a focus on precision medicine (PA2025/1776)
tailored to individuals with similar molecular susceptibility patterns and responses to preventive treatments and actions. The area of research encompasses advanced computational methods based on multimodal
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Assistant Professor in sociology of law with focus on law, rights and social movements (PA2025/1917)
program with a specialization in sociology of law. You currently hold an international position in the research field, and you have not received a salary or grant from Sweden since before 31 December 2021
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programme within the focus area of the position, based on the applicant’s own competence and experience. Teaching expertise is demonstrated by documented ability and experience in planning and implementing
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in light of the applicant’s qualifications and ability to present an innovative and long-term interdisciplinary research programme within the position’s focus area. The applicant is to have
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the third cycle programme. Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme. Read more on the
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Technologies for Transformative Change' and 'Exploring the Transformative Power of Digital Governance in Global Governance'. You are expected to contribute to the entire program, but will primarily work within
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computation. Duties The position includes research and teaching in the subject area. The associate professor is expected to have independent research activities, actively seek research funding, supervise
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to study host-microbiome interactions at the spatial level in the colon. The research activities of the doctoral student will focus on the experimental and computational analysis of spatial gene expression
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and activities connected to our PhD program. In addition to producing individual research, the applicant is also expected to interact with existing researchers within the department, and to contribute
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. The candidate will combine experimental and computational approaches. The project will start with bioinformatics-driven analysis, followed by integration of data generated from experimental models. Over time, the