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robotics) for field-based phenotyping Data management and analytics from multi-stream remote sensing platforms Preferred willingness to learn: Use of Python, CRBasic, Matlab, C++, R, or other programming
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by 9/1/2026. Preferred skills: Experience in process-based crop, soil, or hydrological modeling. Proficiency in Python and other programming languages (Fortran and C/C++ are a plus). Familiarity with
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international conferences. Required Qualifications* PhD in computational biology, bioinformatics, data science, or a related quantitative field. Proficiency in Python and/or R; experience with high-performance
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coding languages, such as R and Python Willingness to learn new methods and pipeline development by interacting with others Willingness to help train others Ability to read literature and learn vision
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with electrophysiology acquisition and analysis (for example spike sorting, LFP analysis, population analyses) Strong quantitative skills and programming experience (MATLAB and or Python), including
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experiment codebases (prefer Python). Apply causal inference and discovery frameworks to clinical questions. Translate proposed methods and frameworks into real-world clinical workflows. Contribute to grant
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) - Strong quantitative/data skills (e.g., Matlab/Python/Origin/JMP) for processing large datasets, fitting models, and producing publication-quality figures. - Track record of technical writing (peer-reviewed
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. - Familiarity with programming in MATLAB and Python. - Experience with finite element simulations in ANSYS or COMSOL. - Strong oral and written communication skills. Application Instructions Please upload
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desirable Experience with LabView, MATLAB, Python, other measurement automation and analysis software Mechanical and electrical design and fabrication capability is desirable Metrology and uncertainty
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composites) Background in polymer viscoelasticity and physics Strong quantitative/data skills (Matlab/Python/Origin) Demonstrated record of technical writing and public speaking Ability to lead projects