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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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demonstrable equivalent professional experience. They will also have strong experience of using machine learning or data science to analyse and model large datasets. Demonstrable technical knowledge and skills
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, · quantifying uncertainty in causal links, · integrating the resulting models into neural networks (or other machine learning models) to detect and predict anomalies or anticipate failures. The research
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a
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) to design representations and transferable energy models for proteins and materials. Contribution to teaching on statistical physics and machine learning. The position will serve to develop your own
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- “AIoT-enabled explanations for healthcare: An exploration on user acceptance & trust”. He/She will be required to participate in the training and optimisation of large language models (LLMs) and
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computational methods using network-based analysis, machine learning and dynamic modeling. We are a young, dynamic team at the idyllic Dahlem campus and teach mainly in the Computer Science, Bioinformatics and