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) charging systems. This position is to recruit a member of the key technical team. Key Responsibilities : You will need to actively support R&D projects at EPGC in terms of project development, testing and
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, algorithmic, AI and communication skills. Proven track records of working in rapid R&D environment with wealth of experience in path planning for robotic arms, reinforcement deep learning and AI. Good
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commonly used in genetics and molecular epidemiology. Expertise in R, Python, bash is required. Strong communication (oral and written) and interpersonal skills, and experience working in a large research
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cognitive experiments Expertise in both frequentist and Bayesian statistics performing descriptive and multivariate statistical analysis techniques such as SEM using SPSS and/or R language. Excellent ICT
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to the Sustainable Built Environment (SBE). The SBE team focuses on building energy modelling and simulation, decarbonization strategies for the built environment and R&D of green building technologies such as HVAC
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. Technical Competencies Proficiency in Python, R, or similar programming languages for data analysis and modeling. Familiarity with AI/ML model evaluation, risk metrics, or reliability analysis. Experience
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analysis, preferably using software such as SPSS, R, MATLAB, or Python. Demonstrated ability to lead research projects, prepare manuscripts, and contribute to scholarly publications. Excellent written and
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statistical packages, especially R and SPSS Good statistical knowledge and skills Good IT skills (i.e., Microsoft Office®) Strong ability to work within a multidisciplinary team Strong interpersonal, written
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on incentive mechanism design. Help supervise PhD, master and undergraduate students, and R&D staff. Help with federated learning technical platform design and development. Help with collaboration with existing
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quantitative discipline Minimum of 2 years’ experience in clinical trials or applied epidemiological research Strong statistical programming skills (e.g., R, Stata) Proven experience in developing Statistical