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Mathematics at the Faculty of Science, Forestry, and Technology invites applications for a Doctoral Researcher (PhD student) position in operator theory, complex analysis, and their applications to mathematical
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Management with Data-Driven and Nature-Based Solutions Apply for this job See advertisement About the position A PhD position in Climate-Resilient Urban Stormwater Management with Data-Driven and Nature-Based
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Physics is looking for a PhD student in computational physics with a focus on understanding
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to demonstrate a good appreciation of generative AI, especially with respect to its use in video creation. This PhD studentship is fully funded for up to 3.5 years with a tax-free studentship stipend of £20,780
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview As a Quantitative Systematic Trader at Susquehanna, you’ll combine
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full-time career. What we're looking for PhDs (in penultimate or final year) in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research
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full-time career. What we're looking for PhDs (in penultimate or final year) in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry