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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
within the previous five years and a minimum of two years of academic research experience in a related field; competency in python, MATLAB or some alternative will be considered. PREFERRED: A strong
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. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitroculture work In situmicroscopy and
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experience in perturbative large-scale structure modeling (LSS), in particular biased dark matter tracers, in simulated dataset analysis, as well as strong programming skills in Python and C. Familiarity with
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annotation; proficiency in R or Python; and excellent English. Experience with spatial transcriptomics and immunology of autoimmune diseases is desirable. Interested candidates should send a motivation letter
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robotic systems for real-world tasks. Strong publication record in top-tier venues: ICRA, IROS, RA-L, T-RO, IJRR, CoRL, NeurIPS, RSS, CDC, TAC. Proficiency in Python, C++, ROS, and machine learning
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for advanced data analysis and/or experimental control (e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in
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. Experience with data analysis in R and/or Python as indicated in application materials. Experience working with AEM surveys of unconsolidated aquifers as indicated in application materials. Experience with
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possess strong quantitative skills (e.g. Matlab, C++, Python). The term of this appointment is one year with the possibility of renewal contingent upon satisfactory performance and continued funding
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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | 18 days ago
environment Excellent programming skills in languages such as Python, C/C++ and CUDA Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch Mandatory experience with High-Performance
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python