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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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background in cancer biology and an interest in integrating experimental work with data analysis. For more details about our research and lab, visit: www.alundberg.org Supervision: Assist Prof. Arian is
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Supervision: Assist Prof. Arian Lundberg proposed to supervise the doctoral student. Decisions are made on admission What we offer Admission requirements To be admitted to postgraduate education (Chapter 7, 39
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position is filled. Contact information For questions, please contact: Prof. Christian Müller Department of Chemistry and Chemical Engineering Email: christian.muller@chalmers.se | Phone: +46 31 772 2790
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, bacteriophages. Prof. Hauryliuk obtained his PhD in 2008 at Uppsala University, Sweden. His scientific contributions were recognized though the Ragnar Söderberg fellowship in Medicine (2014), the Swedish Fernström
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). The successful candidate will work in Maximilian Larena’s research group, and co-supervised by Prof. Mattias Jakobsson and Prof. Carina Schlebusch. The research program consists of an international team
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, distributed across 15 units at Uppsala University and the Swedish University of Agricultural Sciences (SLU). The central hub of this network is Navet, located at the Biomedical Centre (BMC), which serves as a
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and development of algorithms, methods, and theories aimed at better understanding the properties and underlying mechanisms within statistical and deep learning-based systems also in the presence
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set of alternative ways of evaluating a particular expression with unspecified matrix sizes. When a concrete expression is evaluated at run-time, thus revealing the matrix sizes, an extraction algorithm