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have experience implementing scientific code and assessing computational results through validation, verification, and quantitative comparison with reference data. You have prior programming
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, Machine Learning, Medical AI, Biomedical Informatics, Computational Biology, or a related field Strong programming skills in Python and modern ML frameworks Experience with deep learning and large
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record Strong quantitative and analytical skills Experimental laboratory experience (e.g., biomedical engineering, neuroscience, chemistry, optics, electrophysiology, or related fields) Programming
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and spoken English and enjoy collaborating with researchers from different backgrounds. Experience with high-performance computing, scientific programming and/or quantum-computing frameworks is highly
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empirical research addressing relevant economic and public-policy questions An interest in applied macroeconomics and/or political economy Experience with at least one statistical programming language
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quantitative and analytical skills, incl. programming (Python, MATLAB, or similar) Experimental laboratory experience in drug formulation, nanoparticle/microbubble synthesis, colloid chemistry, or related
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nanocrystals, quantum dots, or other nanoscale materials Machine learning Scientific programming and quantitative data analysis Prior experience with every technique used in the project is not required. The
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Scientific programming High-performance computing Prior experience with every method used in the project is not required. The successful candidate should, however, have a strong quantitative foundation
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& Programming: Proven capability in developing physics-based numerical simulators and models of thermal-fluid or power plant systems from governing equations, implementing them in scientific/engineering
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, and validation Integration of sensors, microcontrollers, FPGAs, SoCs, and embedded processors Embedded programming in C/C++ Real-time signal processing and embedded perception, hardware-aware AI