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to achieve the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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). Taking advantage of multiple state-of-the-art techniques (e.g., gene profiling, virus-mediated circuit tracing, calcium imaging/optrode recording, fiber photometry, EEG/EMG recordings, patch clamp slice
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. - Strong quantitative skills and experience coding in MATLAB or Python - Track record of publications and presentations. - Experience in mentorship and/or teaching. Preferred Qualifications • Demonstrated
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coding environments (e.g., R, Python). Ability to work collaboratively with a team of diverse backgrounds. Excellent written and verbal communication skills. Experience in processing large data sets
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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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, imaging informatics, and large language models (LLM) is preferred. This position will require collaboration with multiple stakeholders, including informatics experts, clinicians, basic scientists, and
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broad impact across multiple clinical and neuroscientific disciplines. A strong foundation of technical skills in artificial intelligence applications is essential for success of this project. Cutting
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technologies Proficiency in using Excel, Python, R or similar tools for engineering data analysis is preferrable Excellent written and oral communication skills Motivated self-starter with the ability to work
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Description Glimpse of the Job Are you passionate about research in astronomy and physics? The Department of Astronomy and Physics at Texas A&M University is seeking multiple dedicated Postdoctoral Research