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the field of quantitative biology or machine learning (broadly defined); strong written and oral communication skills; strong knowledge of Python programming; familiarity with DL frameworks (i.e. TensorFlow
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-based imaging techniques (TEM, fluorescence, histology etc.) Successful grant applications Experience in Python programming Having worked on diverse science projects, in international surroundings
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different numerical tools via Python scripting Experience conducting machine learning and inverse design models HPC experience Experience training and supervising students High proficiency in writing skills
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mechanical design Experience with beam shaping techniques (e.g., spatial light modulators, diffractive optical elements) Proficiency in programming languages like LabVIEW, Python, MATLAB, or C++, and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
, biogeochemistry, remote sensing and field ecology are desired. Programming experience in R, Python or other similar computing languages, as well as experience in code versioning software such as GitHub
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Microsoft Word, Excel, Access and PowerPoint. Preferred Qualifications Proficiency and knowledge of multiple statistical software packages preferred, such as SPSS, SAS, R, Python, etc. Experience with ML/DL
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
, Python, Unix/Linux command-line tools, and workflow automation Profound understanding of the relevant metrics and methods to analyze microbial communities and functions and their spatio-temporal patterns
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microscope, as well as electrostatic beam blanker or ultrafast pulser in electron microscopes. Proficient in data analysis and modeling, with experience using Python and other programming or simulation tools
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, Python). Demonstrated ability to independently design and conduct experiments, analyze data, and publish results. Excellent written and verbal communication skills. Strong organizational and time
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, or a closely related field. Proficiency in analysing large climate and environmental datasets using statistical or programming tools (e.g., Python, R, MATLAB). Capability of both managing research