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analysis (R, Python) is an asset. Curiosity, creativity, rigor, willingness to learn, team spirit and collaborative capacity, excellent time and priority management. Fluency in English (written and spoken
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discipline relevant to our research fields (e. g. physics, computer science, electrical/electronic engineering, chemistry etc.). The knowledge of Python, C or other programming languages in use for accelerator
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programming skills in one or more languages (Matlab, Python, R, C, Fortran) excellent knowledge of English (written and spoken) high degree of motivation, creativity, and flexibility ability and willingness
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Python Independent and analytical way of working Reliable and thorough working style Fluent written and spoken English; German language skills are advantageous Please feel free to apply for the position
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, Skills and Experience Broad knowledge of statisticsSkills in programming languages such as R and/or Python Experience of applying statistics to solve complex real-world problems Ability to handle a diverse
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SQUID magnetometry or similar techniques is a strong advantage. Experience in programming, ideally using Python to the extent that you can independently write programs to control and automate measurements
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assays Interest in translational leukemia research, inflammation, and innovative omics technologies Bioinformatics experience, e.g. Python Ideally initial experience with co-culture systems, cytokine
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 16 days ago
molecular biology, cell biology, or neurobiology, - Basic programming skills and willingness to develop in this area, - Skilled use of Python and R would be an advantage - Admission to the Warsaw-4-PhD
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, and data collection. Proficiency in using programming tools (e.g., Python, C#) and statistics to support your work. An open-minded personality with a curiosity-driven mindset, positive attitude towards
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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is