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: Conceptualisation and synthesis of data integration and visualisation workflows. Data management and the development of knowledge graphs Development and application of AI and machine learning methods and pipelines
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technologies Research Field Computer science » Computer systems Computer science » Computer hardware Researcher Profile First Stage Researcher (R1) Application Deadline 11 Aug 2026 - 21:59 (UTC) Country Denmark
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architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction, computer science, interaction
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framework for understanding emergent deception in human-AI interaction by uniting behavioural-psychological, economic-strategic, and machine learning perspectives. The postdoc will be jointly supervised by
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Are you an experienced researcher in microbial genomics and bioinformatics with a strong record of university teaching, and expertise in whole-genome sequencing (WGS) analysis, machine learning and
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circuit models and algorithms for estimating the charge, health, and power based on direct methods (e.g. open circuit voltage), model-based methods (e.g. Kalman filtering), data driven methods (e.g. machine
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cohort studies. The position is for 3 years, starting on October 1, 2026, or as soon as possible hereafter. Information on the Department of Public Health can be found at https://publichealth.ku.dk/ Our
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, especially but not exclusively related to AI, https://digitalcurriculum.au.dk in collaboration with colleagues from CED and NAT Join as a co-teacher in a few of the departments’ workshops and teaching
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
and robotics. As the successful candidate, you will develop innovative research programs spanning atomistic and mesoscopic materials simulations, machine learning, foundation and surrogate models