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fluorescence microscopy, is highly desirable. The successful candidate should also have experience with data analysis tools (Python and/or MATLAB), and ideally be familiar with the challenges associated with
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samples (cell culture) and/or nanomaterials is an asset -experience in scientific programming and data analysis using Python and/or MATLAB -ability to work in an interdisciplinary environment and to
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R or Python will be valued. Co-authorship in scientific manuscripts, experience in student supervision and ability to work as part of a team will also be considered desirable. How to apply
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) Interest and ideally experience in microbiome omics (16S/shotgun; analysis or interface expertise), ideally knowledge in bioinformatic pipelines Solid experimental design and data analysis skills (R/Python
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Biophysical and Biomedical Measurement Group, National Institute of Standards and Technology | Gaithersburg, Maryland | United States | about 2 months ago
measurement workflows. - Strong data-analysis skills using Python, MATLAB, Mathematica, Origin, R, or similar tools. - Strong written and oral communication skills. Highly desired: - Experience designing and
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, or a related field; Good publication record in ML, and/or computational methods for audio data. A publication record in ML applied to bioacoustics is a bonus; Good programming skills in Python
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building and managing complex relational datasets; Proficiency in Python, R or comparable analytical languages and software; Proficiency in the use of large-language models (LLMs) for quantitative and/or
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., in Python. A keen interest in interdisciplinary research. An excellent command of English, as you’ll be working in an internationally diverse community and with international partners. Ability to learn
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using Python, Matlab, or equivalent programming languages. Previous experience in interdisciplinary research projects at the interface between engineering, materials science, and biology will also be
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analytical research on cell-type specific human brain development, and neurological diseases. The project will involve bioinformatic analyses of large datasets with Python and R programming languages. It is