54 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions at University of Basel
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mates; help with administrative tasks, conference organization, communication tasks. You will be encouraged to: take on a co-mentoring role for the project's two doctoral students; teach one or two
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the project, supported by Dr. Adamo and close collaboration partners, within an environment that encourages academic freedom and scientific independence. In line with our and Uni Basel values (https
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, supported by Dr. Adamo and close collaboration partners, within an environment that encourages academic freedom and scientific independence. In line with our and Uni Basel values (https://www.unibas.ch/en
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environment. In line with our and Uni Basel values ( https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html ), we are committed to sustain and promote an inclusive culture, ensure equal
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mechanistic drug profiling and informs model selection across cancer research and drug discovery. In line with our and Uni Basel values ( https://www.unibas.ch/en/Research/Values-Ethics/Diversity.html ), we
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. The job talks and interviews are scheduled for February 2026. Where to apply Website https://academicpositions.com/ad/university-of-basel/2025/phd-positionpre-doc-i… Requirements Research
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. Fabian Baumann (fabian.baumann@unibas.ch ). You can also find out more about us at https://dg.philhist.unibas.ch/de/ . Where to apply Website https://academicpositions.com/ad/university-of-basel/2026/phd
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Baumann (fabian.baumann@unibas.ch ). You can also find out more about us at https://dg.philhist.unibas.ch/de/ . Where to apply Website https://academicpositions.com/ad/university-of-basel/2026/phd-position
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predict protein-protein complementarity, design artificial protein binders, investigate the effects of mutations on protein structure and function, and apply protein representation learning to uncover
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& Machine Learning: Experience in deploying machine learning models and data science workflows in a research context (e.g., cheminformatics, predictive modelling). Design of Experiments (DoE): Knowledge