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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 30 Sep 2025 - 23:59 (Europe/Berlin) Type of Contract Temporary Job
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Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country Spain Application Deadline 17 Sep 2025 - 23:59 (Europe/Madrid) Type of Contract Temporary Job Status Part-time Hours Per Week 30
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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Relevant PhD . Or, relevant Master's Degree and 3 or more years of experience . Or, relevant Bachelor's Degree and 5 or more years of experience . Demonstrates broad understanding and wide application
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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. Serving on committees as needed. - Doing fieldwork as necesary. Salary: $85,000 depending on qualifications. Qualifications Required Qualifications PhD in seismology/geophysics or closely related discipline
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the Research Group “Stochastic Algorithms and Nonparametric Statistics” in the project „SFB/Transregio 388“ SFB/Transregio 388 investigates the interplay between rough analysis and stochastic dynamics. Central