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Field
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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., R, Python, SAS, or STATA) Experience working with large population dataset (e.g. EHR, claims data) Background in health informatics, population health research, or biostatistics, computer science
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
modelling Proven skills in Fortran, Python or a similar programming language Skills in the processing, statistical analysis and visualization of data Very good English knowledge (approximately equivalent to
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software programs that support this work such as Esri’s ArcGIS suite, Adobe Creative suite (InDesign, Illustrator, Photoshop), R, and/or Python. Preferred Qualifications • Experience with Esri’s ArcGIS suite
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maintenance of the FAIR Knowledge Base, ensuring all experimental and simulation data is searchable and reusable. Professional-grade Python skills with a focus on maintenance. You will be responsible
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relevant areas. Has strong ML/AI programming skills (Python: PyTorch, numpy, pandas) and R. Fluent in using UNIX. Publications in related journals is a plus. Baylor College of Medicine is an Equal
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to apply. Basic to advanced experience with computational analysis and R/Python. Excellent oral and written communication skills and be able to work effectively with collaborating researchers. Successful
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software (e.g., WaterTAP) and programming languages (e.g., Python) is highly desirable. Familiarity with the principles of electrified mineral extraction and purification processes is advantageous but not
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with