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Field
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, AAAI). Demonstrated expertise in at least two of the following areas: semantic parsing or structured NLP knowledge representation, reasoning graphs, or GNNs natural language generation, explainability
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Master’s theses Requirements: Master’s or PhD degree with above-average results in Applied Maths (analysis, numerics, modeling) or in a comparable program with a strong math. focus and knowledge in
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) and is strongly committed to nurturing the aspirations of faculty, staff, and students in an inclusive environment. We seek greater representation of women, minorities, people with disabilities, and
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NAMD Deep Learning Development: Experience developing, validating, and deploying deep learning models, especially using Pytorch Multi-Omic Data Representation: Ability to build deep representations
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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of BNITM Willingness and ability to travel abroad for shorter periods to support field research in Southeast Asia and Africa (approx. 2 months per year) Prior knowledge in quantitative data analysis (ideally
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working in research projects International experience Knowledge of university processes and structures What we offer Work-life balance: Our employees enjoy flexible working hours, remote/hybrid and/or part
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to work effectively in an interdisciplinary team. PREFERRED QUALIFICATIONS Experience with one or more of the following: knowledge graphs, graph machine learning, link prediction, representation learning
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable
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will require a 3D animation, computer science and/or anatomical modelling background. A knowledge of dental data and 3D visualisation is desirable. Face Lab, led by Professor Caroline Wilkinson, is an