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experimental activities, data analysis, and the development of new experimental methodologies. Collaborate closely with project partners to compare experimental observations with theoretical models and establish
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actively to M1/M2 student co-supervision. Interact and collaborate productively with other researchers within and outside of the team, including bioinformatic engineers. Present data in lab meetings and
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. Interest and experience with training/fine-tuning machine learning models would also be appreciated. Interest and knowledge of economic theoretical modelling would be a plus. Strong coding skills and
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development and implementation of numerical methods. • Experience in scientific programming. • Familiarity with Fourier-based numerical methods is an asset. • Ability to work in a collaborative international
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motivated candidate with: a PhD in immunology, with expertise in T cell/B cell interactions and/or vaccinology an expertise in advanced flow cytometry a strong motivation to learn organ-on-chip technologies a
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-learning models for patient stratification and outcome prediction. Moreover, complex multi-layered datasets shall be integrated into clinically actionable biomarkers and decision-support tools that underpin
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contains state of-the-art facilities and a highly collaborative research environment with 13 Departments across Biology/Physics/Biomedical fields. Selected publications of the lab: PDGFRα-induced stromal
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity