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information about the position please contact: Prof. Denis SCUTO Your profile Master's degree in Digital History, Data Science, Historical Migration Studies, Digital Humanities, or a related discipline Proven
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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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and epidemiological characterisation of cardiovascular risk among people living with T1D, using multimodal data in the large SFDT1 cohort study. This work will lay the groundwork for developing novel
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summary of your Master's thesis, along with transcripts of your Master 1 and Master 2 grades (4 ) contact information for at least 2 referees; recommendation letters should be sent directly to Cornelia
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collaboration on real-world test cases with industry stakeholders. - Disseminate research findings through publications in leading conferences and top-tier journals. This PhD position offers a unique
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Description of the offer : This PhD project supports the exploration of Vertical Compute’s vertical magnetic device concept. Thanks to the inherent high speed of magnetics and the vertical data
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Description of the offer : The main objective of this PhD thesis is to unravel the microscopic mechanisms by which the hydrogen affects the properties of intermetallic magnets. To achieve this goal
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PhD grant proposal - Carcinogenesis study tools for bioTechnologies and medicine of the future H/F PhD grant proposal : HYMPACT: Modular HYdrogels mimicking the healthy and pathological PAncreatic
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Description of the offer : Spin triangles are magnetic molecules predicted to display spin chirality, magnetoelectricity and protected quantum degrees of freedom. These characteristics could allow electric spin control and long spin coherence properties. In the past we have confirmed the...
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and neural computation. By leveraging the rich data repository on the larva’s neural connectome and muscular structure, the project seeks to create accurate simulations that can inform biological