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electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power
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with cell culture, protein expression and purification. Experience with biophysical methods and cryo-EM sample preparation and data collection and processing is highly desired. Strong communication
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. You are also expected to contribute to the supervision and training of BSc, MSc, and PhD students, as well as to teaching and outreach activities within the department. As a formal qualification, you
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will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity
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Nanolab cleanroom characterize the micro- and nanoelectrodes with electrochemical methods develop an optoelectronic motherboard for optical actuation and electrochemical readout contribute with supervision
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simulation software (e.g., COMSOL, Aspen Plus, MATLAB). Gas chromatography and other analytical methods Energy and mass balances Excellence in both written and spoken English You will be working in
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will be to: Model the optical, mechanical and optoelectronic properties of the fibers using ray tracing and finite element method models; Select and characterize soft materials for the fibers, and use
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Job Description Would you like to join a team that supports the green energy transition by developing wind turbine response and validation methods and solutions? We are seeking a highly motivated
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Job Description Do you want to do research on cutting-edge machine learning methods? If you are building a career as a researcher in machine learning and are passionate about working with cutting
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of extension for the project SECUREAM: Advancing Cybersecurity in Additive Manufacturing in the intersection of blockchain, cryptography, software engineering, and applied formal methods, starting February 1