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evolution. Previous experience in mathematical modelling of biological processes is valuable. Workplace Workplace We offer ETH (Swiss Federal Institute of Technology) and Eawag (Swiss Federal Institute
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, 2024 00:00 Department LA26 - Department of Data Analysis and Mathematical Modelling Contract Limited duration Degree MSc degree in (Applied) Mathematics, Mathematical Biology or Mathematical Sciences
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Mathematical and numerical models of piezoelectric wave energy converters (MPhil or PhD scholarship)
undergraduate degree or equivalent, in applied mathematics, engineering, or a related discipline have experience writing numerical software in a relevant language (e.g., MATLAB, Julia, Python or C) and modelling
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: Continued development of existing mathematical models of corrosion/ageing. Development of models of reactive transport through polymer foams. Development of a model of competitive solubility when a polymer is
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Offer Description Last application date Apr 14, 2024 00:00 Department LA26 - Department of Data Analysis and Mathematical Modelling Contract Limited duration Degree computer science or in an engineering
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project explores ferroptosis induction by RSL3 and iron supplementation in PCa models to develop novel treatments. Mathematical oncology is pivotal in cancer research, aiding experimental studies to unravel
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sciences Mathematical modelling skills Ability to work independently as well as collaboratively in an international, interdisciplinary team across institutes Very good communication and organizational skills
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: Masters degree in bioengineering, environmental sciences or applied mathematics Knowledge of plant and soil sciences Mathematical modelling skills Ability to work independently as well as collaboratively in
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, Psychological sciences JOB /OFFER DESCRIPTION COMPO Team The ambition of the COMPO Inria-Inserm joint project-team is to develop novel mathematical models integrating data available in clinical oncology (from
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mathematics, physics, engineering, and applied sciences. The doctoral researchers are trained by the experts on fields related to the Flagship of Advanced Mathematics for Sensing, Imaging and Modelling (FAME