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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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signal processing chains using tools such as MATLAB or Python. 5. Analyze radar datasets and support development of feature extraction techniques. 6. Assist with laboratory experiments and prototype radar
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porous media. Proficiency in scientific programming (Python, C++, or Fortran) is essential. Demonstrated strong analytical and problem-solving skills, with familiarity in numerical methods and an interest
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Excel, SPSS, R, Python, or Tableau. Strong attention to detail, analytical thinking, and communication skills. Ability to work independently and collaboratively in a fast-paced environment. Applications
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cell culture and cell biology. Strong instrumental analysis skills, specifically for investigating biological mechanisms utilizing U-M Core Facility resources. Experience in Python or R programming is
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processing, and sensor integration. Strong background in signal processing, computer vision, or machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record
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- Strong programming, statistical, and technical skills (e.g., Matlab, Python, R) Please apply with your cover letter, CV, and 2-3 references. For people in the EU, click here for information on your privacy
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computer and programming skills (e.g., Python, R) are highly beneficial Hands-on experience with ChemSpeed or related robotic platforms for reaction automatization is highly beneficial Previous experience in
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. Programming experience in at least one language such as Python, MATLAB, or C/C++. Strong analytical, quantitative, and problem-solving skills. The ability to work effectively both independently and as part of a
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem