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Field
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workbench for chiplet assembly Generation of FE models for different chiplet configurations using the workflow Research and identification of suitable Python modules for Ansys FE modeling automation Use
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, Mathematics, or a related field, and you possess a solid understanding of technical concepts. Programming Skills: You have initial experience in object-oriented programming, particularly with Python, and are
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(especially Fortran and Python) - studies in a science degree program (BSc or MSc), preferably in planetary sciences - basic knowledge or strong interest in planetology and geodynamic modeling - english skills
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C
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. The working language of the lab is English; knowledge of the German language is not necessary. Experience in computational image analysis, deep learning, and strong coding skills (Python, R) are required
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proficiency in Python and/or R; familiarity with working in a Linux/Unix environment; fluency in English (both written and spoken); excellent communication and teamwork skills in an interdisciplinary
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skills in Python and Matlab Very good English skills and basic German skills Our offer A vibrant research community in an open, diverse and international work environment Scientific excellence and
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project activities and writing reports Your Profile MSc or PhD in a relevant field Experience with Machine Learning modeling Coding experience, preferably Python Basic knowledge of databases tools and
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in programming languages such as Python and C++. Goal is the development and integration of new and automated measurement capabilities for ultra-sensitive low-energy AMS. This includes extending and
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into high-quality, reusable Python software packages. - Engaging in the full software engineering process, including refactoring, comprehensive testing to ensure code reliability, and creating clear