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Particle Tracking (3D-LPT) techniques for industrial applications. The work specifically targets applications in industrial wind tunnels, with a focus on the automotive and aerospace sector. The developed
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-source software, and help shape emerging methodologies for scientific AI and foundation models. Applicants should indicate a primary research track, although collaboration between tracks is expected. Track
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working in High-Performance Computing (HPC) environments. Soft Skills: Proven track record of scientific publishing and the ability to mentor junior researchers (EngD/PhD students). Mindset: An analytical
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(e.g., mathematics, physics or computational social science), with a strong track record in network science (or complex networks / social network analysis); Excellent writing skills and proficiency
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to have obtained a PhD in engineering, with experience in concrete modelling and experimentation. The candidate should also have a proven track record in scientific publishing. A good command of English
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neuroscience of language comprehension Experience with open science practices (e.g. preregistration, data sharing) A track record of peer-reviewed publications The successful candidate must relocate to Leiden
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in suitable push solvent, including flow-cell design. Both LACDR and dsm-firmenich have a strong track record in development and implementation of cutting-edge instrumentation to advance metabolomics
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intellectual histories using visual art/periodical press/graphic arts/cultural discourse as archives; Track record in working with vernacular/regional languages tied to their specific field/geography
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/Africa. Experience in working in intellectual histories using visual art/periodical press/graphic arts/cultural discourse as archives Track record in working with vernacular/regional languages tied
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track record in one or more of the following fields: (1) human-computer interaction, collaborative AI, (2) Generative AI/machine learning, (3) interaction design, experimental design, or evaluation