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focus areas. We are looking for curious minds who are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities
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are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN
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as evidence of ongoing CIN. This PhD will work at the leading edge of single-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We
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sampling of zooplankton along environmental gradients Statistical analysis and interpretation of experimental data Publication of research results in peer-reviewed scientific journals Presentation
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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(e.g., statistical analysis, numerical modeling, optimization) – essential for data interpretation and model development; Background in scattering techniques (SANS/SAXS) and/or data modelling is a plus
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well as fungal transformation is appreciated Experience with fluorescence microscopy Knowledge of programming, R, statistical analysis or bioinformatic is strongly appreciated Excellent English proficiency in
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experience (e.g. student assistant post) • Preferably demonstrable experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) • Well-developed statistical software skills