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Job Description Are you passionate about acoustic signal processing? We are seeking a highly motivated PhD candidate with a strong background in acoustics, microphone array processing, statistics
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. The PhD project falls under Research Track 1: Informational Modes of Learning. Functional connectivity captures the statistical relationships between distinct brain regions, whereas effective connectivity
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redundancy in brain signals elicited by acoustic stimuli. The PhD project falls under Research Track 1: Informational Modes of Learning. Functional connectivity captures the statistical relationships between
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, statistics, and AI to bridge agroecology and robotic control. At MMMI you will be aligned with research units in Unmanned Aerial Systems (PhD#1), Industrial Robots (PhD#2), and Software Engineering (PhD#3
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behaviour. This will include developing and using state-of-the-art image recognition algorithms to create digital twin models as well as statistical and machine learning methods for analysing large-scale
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developed with the supervisors within the first two months after enrolment. You must have a two-year master's degree (120 ECTS points in STEMS, with a preference in engineering, statistics, physics
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engineering, statistics, physics, mathematics, data science, informatics or similar degree with an academic level equivalent to a master's degree. The candidate should preferably have: Dedication and the desire
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics This PhD project falls under Research Thrust RT3