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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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communication skills are encouraged to apply. A MSc degree (or equivalent) in Mechanical Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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proven ability to interact effectively with academic and societal stakeholders. Knowledge of qualitative research methods such as interviewing, organising workshops, participant observation and comparative
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related field; experience with numerical modelling, preferably hydrological modelling; affinity with delta systems, adaptation and policy analysis; motivation to work in interdisciplinary scientific
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-of-the art electrophysiological and behavioral recording methods as birds freely engage in dynamic vocal interactions. This neuroethological approach will reveal how complex streams of acoustic input
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criminalisation of homelessness in other nations. The PhD researcher will be expected to employ doctrinal legal research methods as well as conduct a comparative analysis between jurisdictions. Depending
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
contributing to global discussions. The candidate will develop strong research skills, with particular focus on participatory methods, and approaches grounded in cultural heritage and critical studies. The PhD
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researcher will be expected to employ doctrinal legal research methods as well as conduct a comparative analysis between jurisdictions. Depending on the project’s development and feasibility considerations
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analysis systems, to ensure safe and trustworthy results. This can involve research questions from NLP and AI like model robustness and guardrails, human-computer interaction such as interpretability and