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model species (e.g. Culex pipiens) to test specific hypotheses about sensory-driven flight behaviour under controlled light and visual environments. This will allow you to explore the underlying
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behaviour under controlled light and visual environments. This will allow you to explore the underlying mechanisms that shape swarming rules and to validate your field-based findings. The broader aim
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advantage. - Experience with programming languages (e.g. python, C++) is considered a plus. - A strong team player, with well-developed communication and collaboration skills. - Excellent command of written
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techniques (lithography-based) to manufacture highly controlled three-dimensional electrode structures. Strong collaboration is expected with other project partners in areas such as multiscale modelling
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language
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advantage. Experience with programming languages (e.g. python, C++) is considered a plus. A strong team player, with well-developed communication and collaboration skills. Excellent command of written and
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intuitive links between search parameters and the resulting geometry or performance outcomes. The result will be an LLM-driven framework giving designers clearer cause-effect control over generative shape
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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skills in algorithmic design; Possess good communication skills and an excellent command of English. Additional Information Benefits We encourage high responsibility and independence, while collaborating
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate