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productively in a team as well as independently. Excellent communication skills for interacting effectively with senior colleagues and peers are required. Great emphasis will be placed on personal suitability
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dynamic and non-stationary. As a result, the performance of models trained offline tends to deteriorate when exposed to new signal conditions, previously unseen patterns, or changing system characteristics
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‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future
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, laboratory reports, structured test results, species identifications, susceptibility profiles, interpretative comments, and registry-linked outcome data. In this project, you will develop and apply AI-based
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, and registry-linked outcome data. In this project, you will develop and apply AI-based methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen
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areas, but application to dynamic systems is hampered when the number of time samples is small compared to state dimensions, while latency and stability remain central concerns. As a result, learning
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, with a particular focus on identifying and characterizing rare endosomal escape events. The tasks include developing, training, and validating deep learning–based models for event detection and vesicle
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and can prioritize effectively among tasks. This position also requires the ability to communicate your message clearly, both in academic settings and in collaboration with others. As our activities
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unresolved issue: how the interaction between humans and technology in safety-critical maintenance work affects risk and productivity in the Swedish mining industry. Effective maintenance is the foundation
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and sustainable. The PhD student will investigate the effects of crop diversification on soil health under the supervision of a multi-disciplinary team of researchers. The student will be involved in