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. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in 2D convolutional neural networks in Python. This is a part-time position (5
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2D convolutional neural networks in Python. This is a part-time position (5 hours/week) funded until 31/03/2026 with a possibility of extension and is suitable for a Ph.D. student with relevant
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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and communication skills, experience working with data in either R or Python, a medical degree, experience in functional genomic analyses, and experience working with people with lived experience in a
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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to process data and/or answer quantitative research questions (e.g., but not limited to applications written in either R, Python, Julia, Go, Java, or C/C++). E3: Experience of scientific writing. E4: Proven
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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: Essential criteria MSc. in Neuroscience, Physics, Computer Science, or a related field Strong background in computational neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices