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. Qualifications Strong quantitative training, including coding skills in R and Python, and satellite imagery analysis. Good communication skills in English. Ph.D. or foreign equivalent in geography, remote sensing
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field Experience working with cryogenic thermal-vacuum systems Experience developing electrical systems and data acquisition with Python or LabView Preferred Qualifications: Expertise in planetary
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Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
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simulations, statistical mechanics, computer programming (e.g., C++, Python), polymer theory, molecular modeling (e.g., of proteins, nucleic acids, ligands), coarse-grain and polymer model development
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, Python, and R. The candidate should have a strong capacity to understand processes underlying pro-environmental behaviour from different perspectives, enabling them to simultaneously understand, use, and
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: Ph.D. in Computational Biology, Bioinformatics, Computer Science or related field. Demonstrated proficiency in Python or R, with experience building bioinformatic workflows and documenting code with
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(e.g., Matlab, Python), neuroinformatics, and/or advanced microscopy tools is plus, but not required. More details of the lab including publications can be found in the lab web site (https://kimlab.io
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practices in different research communities; Teach lessons and workshops such as data processing and analysis using R or Python, tools and best practices for data management, computational best practices
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of concepts and techniques from Quantum Information Science. - Experience with Python, Julia, Mathematica and quantum programming environments like Qiskit. Overtime Status Exempt: Not eligible for overtime
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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