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Field
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tools are indispensable for plant breeding. The Swedish apple breeding program is currently in a state of transition considering both, the use of genomic tools and breeding targets. To support this, we
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role in reaching the climate targets as they can act as natural carbon sinks. However, human interventions can significantly impact the forests’ ability to contribute to greenhouse gas reductions
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advanced data science methods, including statistical modeling and machine learning approaches Developing and applying novel causal inference methods, such as target trial emulation and causal AI frameworks
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AI4TECS aims to develop the first AI‑powerAd system that integrates real‑time EC identification using non-target high resolution mass spectrometry data, toxicity prediction, and transformation modelling
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experience (front-/back-end, metrology/inspection, equipment maintenance, yield-improvement projects). Digital twin, IIoT, MLOps, real-time data streaming, edge computing. Causal/XAI, Bayesian methods
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der Waals heterostructures using wet or dry methods onto target substrates such as SiO₂/Si, ferroelectric materials or microelectronic chips, • the characterisation of materials after transfer, • micro
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through extensive and targeted training and career programs. Compatibility of work and family life: A good work-life balance is important to our employees. Fraunhofer ISI offers flexible working hours and
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on the prevalence and evidence related to post-stroke fatigue. Investigating the mechanisms and impacts of post-stroke fatigue Contributing to the design and evaluation of targeted interventions Collaborating with
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safety-critical domain, reducing hallucinations and improving robustness and trustworthiness are essential. This PhD targets principled ways to detect, analyze, and mitigate hallucinations in video-based
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pipelines for ML/AI models (TensorFlow/Pytorch) for multi-omics, cell screening, and drug-target affinity data from to achieve state-of-the-art performance. Build ETL pipelines for large datasets Documenting