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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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scientific advisors and opportunity to mentor students Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A
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data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further development of your personal strengths, e.g. via a
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Your Job: The Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) provides an interdisciplinary environment for educating the next generation of data scientists in close contact
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into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive experimental calibration. Embedded in the Helmholtz Graduate School for Data Science in Life, Earth
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(including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A qualification that is highly valued in industry 30 days of annual leave and flexible working
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. presenting your research results) Preparing scientific publications and project reports Your Profile: Genuine interest in data science and one or more of its application domains: life and medical sciences
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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, computer science and earth science/engineering, or a related field Proficiency in at least one programming language (Python, Matlab, R, C++, Julia, …) Good analytical skills with a sound understanding of data
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experimental calibration. Embedded in the Helmholtz Graduate School for Data Science in Life, Earth and Energy (HDS-LEE), the project offers an interdisciplinary research environment at the interface