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Main supervisor: Prof. Joerg Widmer [IMDEA Networks] Co-supervisors/mentors: Prof. M. Petrova [RWTH], Dr. T. Otim [IMDEA], and Dr. X. Costa-Perez [NEC] Required profile: Telecommunication, Electrical
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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-behavioral biases are most critical in facilitating climate risks to become systemic. This data collection and analysis work will benefit from the computational agent-based and macroeconomic modeling (carried
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, systems, and hardware design. Experience in one or more of: LLMs, AI agents, embedded ML, physical modelling and simulation Strong programming skills in Python and C/C++, familiarity with ML deployment
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. Additionally, the impact of chemotherapeutic agents on cardiac tissue function will be studied using this model. Goals Identify appropriate scaffold base materials, evaluate various crosslinking methods (such as
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, an agent-based physiological 3D model of mitochondria based on the seminal work of Prof. Skupin (https://www.nature.com/articles/s41598-019-54159-1 ) will be extended and embedded into a continuous
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-waiting – were successful spies in seventeenth-century England. This is what Nadine Akkerman describes in her book Invisible Agents, the first analysis of the role of female spies in the seventeenth century
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This project is part of the EU-funded Print4Life , a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof. Persson, group leader of BioMaterial Systems (BmS). This network has eight doctoral candidate host
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Primary supervisor - Prof Colin Cooper It is well established that bacteria can cause human cancer, with, for example, Helicobacter pylori implicated in the development of gastric cancer and
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for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models