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Field
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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transfection work Experience with microscopy Experience with RNA-seq Experience with image and RNA-seq analysis, including competence using R or python and computational clusters Molecular biology techniques
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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(e.g. C++, Python, Matlab) OpenFOAM (beneficial, not required) Strong analytical and problem-solving skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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an opportunity to network and get feedback on their work. Student profile: Some experience in data analysis would be very helpful, as would a working familiarity with a programming language (e.g. Python, R
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courses, excellent grades, and an outstanding master thesis). You have strong affinity with (social) entrepreneurship research, preferably including proficiency in programming languages (e.g., Python, R
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proficient in ROS/ROS2, Python and/or C++/C# Knowledge and/or experience within one or more of the fields of acoustic sensing, hydrodynamics, and machine learning is a plus. You have strong communication
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent