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- Zintellect
- Łukasiewicz Research Network - Krakow Institute of Technology
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Field
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and assistance. Required License/Registration/Certifications Job Duties Computational simulation and theoretical research Publication and scientific dissemination Proposal assistance and development
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-based and UV-curable inks. Implement FEM simulations linking chemistry, processing, and performance. Integrate experimental data from the experimental PhD’s for model validation. Collaborate with
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matter physics, with a staff of 450, including 175 researchers and lecturers. The MEM laboratory (CEA Grenoble) conducts research on the exploration of materials and devices using advanced simulation
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 15 hours ago
you for multiple applications in Zintellect, they must click the unique link in each email request, but will be given the opportunity to copy over what they had previously submitted. All documents must
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
you for multiple applications in Zintellect, they must click the unique link in each email request, but will be given the opportunity to copy over what they had previously submitted. All documents must
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with a strong focus in analog and RF integrated circuits. The candidates must have expertise in mmWave circuit design using advanced CMOS or SiGe process, electromagnetic simulations using HFSS and EMX
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a postdoctoral researcher in the same or related subject area at MDU that exceeds one year. Applicants must be able to demonstrate knowledge and experience in: Simulation software for building and
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software and programming environments. Experience with optimisation, simulation, econometrics, or data analysis applied to energy or market data. Knowledge of data centre operations, computing infrastructure
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translate these devices to practical medical applications. Core Responsibilities: Simulation and design of optical imaging systems and piezoelectric ultrasonic transducers using ray tracing and the finite
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to develop novel AI and machine-learning methods for accelerated materials discovery. The focus is on combining generative AI, active learning, first-principles simulations, and machine-learning potentials