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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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intelligence, data science, medical physics, neuroimaging, bioengineering, or related disciplines, accompanied by accredited training in machine learning, deep learning, or medical image analysis. Experience: A
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk
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quantitative measurement to these system -from single molecules and nanoparticles to living systems, enabled by advances in instrumentation, spectroscopy, mass spectrometry, microscopy, and machine learning
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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PhD Positions Application Deadline 25 Sep 2026 - 13:00 (Europe/Dublin) Country Ireland Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2026 Is the job funded
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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insights. Ability to apply system-level thinking, linking infrastructure performance, environmental conditions, and operations. Experience with data-driven modelling or machine learning. Ability to work both
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, the following position is available from 1st January 2027: PhD Position in Learning Analytics and Self-Regulated Learning (m/f/d, E13 TV-L, 75%) DFG-funded project TRACE: Trajectories of Adaptation, Disengagement
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combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the globe. Candidates with