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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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biological data analysis as well as microbiology and biotechnology techniques. You’re always up for a challenge, eager to learn new methods and technologies, and thrive in a fast-paced research environment
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signal processing (GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral
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team members Perform accelerated optical degradation tests of transparent conductive materials Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a
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are required to have: A completed PhD degree. Experience in machine-learning methods. Some skill in at least one of these topics: Large data sets analysis Statistics and uncertainty analysis (probabilistic
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(GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral communication skills
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8 Mar 2025 Job Information Organisation/Company Empa Research Field Computer science » Programming Engineering » Materials engineering Engineering » Mechanical engineering Engineering » Other
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background in microfabrication. Further, experience with experimental setups, large-scale data acquisition and analysis, FPGA programming skills, and knowledge of Python and C++ are important assets
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modelling and/or empirical analysis. The research will ideally combine insights from economics and e.g. computer science. Profile Applicants should hold a PhD in Economics with a strong economic basis and
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University (see below). The project combines lab work and advanced data analysis using state of the art methods. It provides a great opportunity to further develop a research line and establish a portfolio