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community. Required Skills and Qualifications: Minimum PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C
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Python for stimulus presentation and data analysis Conduct statistical analysis using software such as SPSS, R or Python to support data interpretation and research findings Collaborate with and provide
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physics, and quantum error mitigation. Good programming skills in Python. Familiarity with PyTorch or tensorflow will be a bonus. Proficiency of programming skill with quantum machine learning architectures
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systems, MARL, Game Theory. Strong background in Mathematics and modelling. Good English writing and communication skills for research work. Proficiency in Python, experience with PyTorch, NumPy, and
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resourceful, organised, and able to manage multiple priorities effectively. e) Be highly numerate, analytical, and be willing to work with complex datasets. The ideal applicant should also: a) Have experience
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community. Required Skills and Qualifications: Minimum PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C
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or adaptive designs. • Proficiency in at least one of the following: R, Python, JavaScript, or other relevant data analysis or app development tools. • Familiarity with EMA, EMI, MRTs, or SMART designs is
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frameworks commonly used in ML research, such as Python, PyTorch, TensorFlow, and mobile development environments (e.g., Android Studio or Swift/Xcode). Demonstrated ability to conduct independent research, as
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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community. Requirement: PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like