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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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, Python) - Interest in economic sociology and political economy - Knowledge of more than one European language other than English is an advantage - students in North American Studies (with an interest in
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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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evaluated. What you bring to the table Enrolled student Background in Computer Science, Software Engineering, Electrical Engineering, Autonomous Systems or similar Knowledge of C++/Python Experience with ROS
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university degree (diploma, master's degree) in transport or traffic flow or related study programs. Solid knowledge of at least one programming language, preferably Python, experience in model-based
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molecular biological methods interest in the interactions between ecology and public health basic programming skills (e. g. Python, R) will be a plus knowledge in entomology will be useful good command
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informatics or AI Good knowledge in programming with python and on software development Knowledge on LLMs and langchain is a plus Analytical and structured mindset Good knowledge of the English and German
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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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Strong programming skills (e.g. Python, R, C/C++) and experience with highthroughput sequencing data Solid understanding of RNA biology, transcriptomics and epitranscriptomics Desirable skills: Experience