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-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio Telescope may be possible, depending on the interest of the PhD
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the renewable energy management system by developing novel real-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio Telescope may
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. This includes sensors and sensor systems, new-space satellite system design, assembly, integration, test, operation and utilization, as well as novel sensors for planetary resource mapping and exploitation
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gauges, solenoid valves, resistive heaters and thermocouple sensors, PID controllers, actuated gate valves, etc. Programming in LabView environment for real-time instrument control. Implementation of a
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at Centre for Space Sensors and Systems (CENSSS) at the Department of Technology Systems (ITS). Starting date no later than November 1, 2025. The fellowship period is three years. A fourth year maybe
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis
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. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including