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, sociological...) to measuring beliefs, attitudes, and their relationship with shaping (online) behavior is desirable. Familiarity with data analysis in R or Python is required. Experience in study handling
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packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
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about to obtain) a PhD in the broad area of Computational Modelling applied to geochemical or biological systems, and be comfortable working routinely in modern programming languages (e.g. Python, Julia
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, problem-solving and project management skills. Candidates with strong quantitative skills, including familiarity with python and astronomy are desired for this project. Must be eligible to enrol in PhD
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essential. Excellent organisation and problem solving skills are expected and experience in data wrangling, processing and visualisation using R or Python would be advantageous but not essential
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with Python or C. Solid understanding of linear algebra, calculus, and probability theory. Strong background in machine learning and deep learning is highly preferred. The ideal candidate will have
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, adversarial attacks, and Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering
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skills in Python and PyTorch including fundamental software engineering principles and machine learning design patterns. Be highly motivated and a team player with excellent communication and presentation
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methods based on exact algorithms and/or (meta)heuristics (in Python, Java, C++, …) You are willing to invest time and effort in improving both your academic English writing and presentation skills, i.e