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PHD STIPEND IN DETECTION OF PEPTIDE-BASED PESTICIDES Apply Vacant position PHD STIPEND IN DETECTION OF PEPTIDE-BASED PESTICIDES Aalborg Deadline : 22.10.2026 Department: Department of Chemistry and
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coordinate individual unmanned underwater vehicles (UUVs) and entire swarms based on local information, for anomaly detection and infrastructure surveying in environments where communication is
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underwater anomaly detection Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 3 Nov 2026 View more categories View less categories Discipline
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We are seeking a postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data
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barriers to achieving this, is figuring out how to learn useful patterns in the data without relying on exhaustive labelling. For example, in the anomaly detection setting, we often assume that only healthy
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redirected to an external site after 5 seconds) Save job Click to add the job to your shortlist Send job Job Details The SDU Adaptive Intelligence Lab (ADIN Lab) ( https://adinlab.github.io/ ) located
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machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills (e.g., Python) and experience with deep learning
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project aims to advance non-destructive, rapid, and highly sensitive hyperspectral methods for the detection, identification, and characterization of forensic traces, including fire debris, biological
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selected isolates. Comparative genomic analyses will assess microbial connectivity between compartments while distinguishing co-detection from evidence consistent with persistence or transfer. Findings will
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spoken English. Documented experience with one or more of the following will be an advantage: Longitudinal, multilevel, Bayesian, or other advanced quantitative methods relevant to comparative research