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mathematical modelling, with a focus on real-world applications. This includes statistics, uncertainty quantification, data analysis, signal processing, (mathematical foundations of) machine learning, and
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Annual Report Individual Appointment Advising Our Programs & Resources Events Upcoming Events Learn about our events Ph.D. Career Stories ASPIRE UP: A Career and Professional Development Series
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chains. Has demonstrated experience analyzing textual data using NLP or other machine learning techniques. Has excellent English-language academic communication skills (both written and oral) – CEFR level
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. (2017). Beyond prediction: Using big data for policy problems. Science, 355(6324), 483–485. Barocas, S., Hardt, M., & Narayanan, A. (2021). Fairness in Machine Learning. Retrieved from https
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: communicative, empathy, influence without authority, analytical thinking, and a collaborative mindset. Bonus skills: experience with change management, machine learning, basic programming, or research software
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database (e.g., constitutional change proposals, court rulings), and employing supervised machine learning/ natural language processing to scale content. Examples (not must-haves) of relevant skills include
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at the Erasmus Centre for Data Analytics: https://ecda.eur.nl/expert-practices/psychology-of-ai/ Opens external Employment conditions ERIM offers fully-funded and salaried PhD positions, which means that accepted
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required for this post. A PhD is desirable. Additional requirements Additional assets for this position are: experience in machine learning engineering and related tooling; experience with European cloud
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research (e.g., combining big data or machine learning with in-depth fieldwork) can also be pursued. Method selection and mastery are viewed as part of the PhD learning process, guided by supervisors and
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such as data science, AI, computer science, machine learning, Earth system science, climate etc., with a thesis subject relevant to the description of the tasks outlined above. Additional requirements In