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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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the wild? You are excited about deploying autonomy algorithms on real platforms and validating them in demanding real-world environments? We are looking for an outstanding and highly motivated doctoral
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) • Contributing to analyses of agency, responsibility, trust, mental privacy, and algorithmic bias in neuroAI systems • Collaborating with technical partners on issues of transparency, interpretability, and
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decision-making algorithms on real robotic systems operating in unstructured and dynamic environments. This work is connected to the Robotics Institute Germany (RIG) and relates to the thematic cluster
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biochemists developing the labeling agents, data analysts developing analysis algorithms and physicists developing hardware. The candidate The candidate should have a firm base in in vivo imaging and cell
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed