35 machine-learning "https:" "https:" "https:" "https:" "https:" uni jobs at Chalmers University of Technology
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Helps us to derive novel climate data by combining two of Europe's new satellite sensors. If you have interests in physics, climate and machine learning, this is the Doctoral student position
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with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted. The following experience will strengthen your application: Experience in system identification and machine learning is
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application: Experience in system identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results of your research
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combining two of Europe's new satellite sensors. If you have interests in physics, climate and machine learning, this is the Doctoral student position for you! About us Our team is part of the Division
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results verbally and in writing Take courses at an advanced level
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your application: Experience in system identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results of your
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60 credits* in Computer Science, Electrical engineering, or equivalent. You will need strong written and verbal communication skills in English. Strong machine learning fundamentals (probability
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methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods. Special
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-order modeling, or machine learning Experience collaborating in interdisciplinary research teams What you will do Develop hybrid quantum–classical methods to improve simulation and prediction