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expertise in regulatory proteomics, ADP-ribosylation biology, and mass spectrometry-based technology development. Postdoctoral position #1 is funded through a recently awarded grant from the Danish Cancer
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to recruit a talented researcher for a 2-year, full-time postdoc in machine learning from 1 October or soon thereafter. Your work tasks We are looking to recruit an excellent postdoctoral fellow to apply
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contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and they make use
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relevant to the subject area: • Victimization and offending • Hybridization of crime • Illicit online markets The research projects may address national or international challenges and should employ
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. On the technical side, the ideal candidate will have demonstrated experience in the use of molecular nucleotide analyses based on eDNA and eRNA; functional activity analyses like enzymatic or respiratory analyses
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others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
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expect some travel activity between the department’s sites in Aarhus and Copenhagen. The Danish School of Education is committed to diversity and encourages all qualified applicants to apply, regardless
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for persistent pain in humans. CNAP is a research Center of Excellence inaugurated in 2015 by the Danish National Research Foundation at Aalborg University, Denmark (www.cnap.hst.aau.dk ). CNAP applies a basic
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for researchers may apply. We are committed to fostering an inclusive and diverse research environment. We welcome applications from all qualified candidates regardless of gender, age, disability, religion, ethnic
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communities and their physiological responses to environmental conditions Apply advanced laboratory and analytical techniques to environmental samples Apply for external funding and participate in collaborative