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. You have good programming skills in Python and/or R; you are familiar with reproducible coding and automated (geospatial) data analysis. You have excellent scientific writing and communication skills in
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and programming skills (Python preferred). Excellent written and verbal communication in English. Passion for exploring the frontiers of condensed matter physics. What We Offer · Pioneering
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, or industrial engineering. Proficiency in Python and simulation tools (e.g. AnyLogic, Arena) and optimization solvers (Gurobi, CPLEX). Solid background in decarbonization modeling, logistics, and techno-economic
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, energy systems, simulation, and/or transportation research. Technical skills: Python programming; simulation. Domain knowledge: Decarbonization modeling, life-cycle assessment, battery-electric vehicle
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learning and biotechnology, and you are able to contribute decisively to existing research projects. You have deep familiarity with a scientific computing language (preferably Python) and have demonstrable
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and solids. Experience in scientific programming in C/C++, Python, Fortran, Mathematica or similar is required. The successful candidate will either hold a PhD in Physics or a related area, or
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
validation; proficiency in Python and scientific computing, including experience with finite element methods, preferably using FEniCS or DOLFINx; strong analytical and communication skills, with the ability
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thinking skills. Competence in data analysis and visualization using software such as GraphPad Prism, R, or Python. Excellent scientific writing and communication skills, with a track record of peer-reviewed
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to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big