5 Mathematiker Jobs in Wien
Ihr beruflicher Tätigkeitsraum:
- Work-Life-Balance: Die Vereinbarkeit von Beruf und Privatleben bzw. Beruf und Studium sind uns ein
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Ihr Aufgabenbereich
- Doctorate related to the above requirements
- Strong background in optimization and partial differential equations
- Strong background in numerical mathematics and computing
- Machine learning skills are welcome
- English skills needed
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Ihr Aufgabenbereich
- Conduct original scientific research in the field of inverse problems applied for extremely large telescopes (theoretical analysis, development and implementation of algorithms, simulations and experimental tests) Be part of a doctoral training and work towards obtaining a PhD in technical sciences
- Collaborate with scientists and students working in other fields covered by the mathematical and astronomical research network
- Publish scientific findings in renowned international journals and at conferences
- Complete trainings or short-term research stays at international collaboration partners
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About the team:
- Participation in research projects / research studies
- Participation in publications / academic articles / presentations
- We expect the successful candidate to sign a doctoral thesis agreement within 12-18 months.
- Participation in teaching and independent teaching of courses as defined by the collective agreement
- Supervision of students
- Involvement in the organisation of meetings, conferences, symposiums
- Involvement in the department administration as well as in teaching and research administration
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Your Tasks
- Develop and merge innovative approaches in spatial data encoding, continuous output representation, and multi-variable simulation with dynamic data integration (Retrieval Augmented Generation, RAG) to push the boundaries of spatial stochastic simulation research.
- Design, prototype, and test advanced transformer-based methods tailored to complex spatial and multi-variable data.
- Create robust training protocols to manage non-stationary data and develop strategies for continuous output (e.g., raw value predictions, Fourier decomposition).
- Implement tokenization and cross-attention techniques to efficiently handle multi-variable simulations.
- Collaborate with international partners and contribute to an environment that values scientific freedom, interdisciplinary work, and curiosity-driven exploration.
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