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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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development using Python and/or other programming languages, as well as executing organic (multistep) reactions in the laboratory. We are looking for an applicant with: A Master's degree in chemistry, chemical
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around us? At Maastricht University, you will investigate how individuals differ in predictive processing by combining behavioural and neural testing with computational modelling. Together with colleagues
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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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Matlab, Python, Fortran or C/C++) will be beneficial. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. The studentship covers
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data to decode multisensory information Investigate how neural representations change across different brain states (awake, asleep, engaged) and track representational drift over extended time periods
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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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characterizing defects such as dislocations Applying generative models (e.g., GANs, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities
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other empirical damage and vulnerability data. Couple the ABM with the Regional Flood Model (RFM) to describe temporal developments of flood risk considering adaptation decisions. Different adaptation