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BAM Bundesanstalt für Materialforschung und -prüfung | Berlin, Berlin | Germany | about 2 months ago
PhD student (m/f/d) in the field of mathematics, scientific computing, physics or an engineering discipline with a proven strong focus on numerical methods Berlin Division 8.4: Acoustic and
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. You will be expected to undertake a self-directed program of research and scholarship, play a role in the national and international Mathematics community, in addition to teaching students
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Applied Physics (PAP). MAS covers diverse topics ranging from pure mathematics to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and
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LevelPhD or equivalent Skills/Qualifications PhD in Applied Mathematics, Statistics, Computer Science, Computational Science, Physics, Engineering or relevant field by the appointment date, or a closely
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
qualification equivalent to a Master’s degree in Chemistry, Mathematics or Computer Science by the start of the PhD; A curious mind-set and strong background in quantum crystallography and its underlying
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Research Associate / Magma Research Fellows who have: a PhD in mathematics, computer science, or a related discipline a strong background in computational mathematics, computer algebra, or mathematical
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. You will be expected to undertake a self-directed program of research and scholarship, play a role in the national and international Mathematics community, in addition to teaching students
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, and mathematical data science, with an active programme at the interface of dynamical systems, machine learning, and quantum information. The position sits in the GOAL group (GeOmetry, dynAmics, and
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UKRI Future Leaders Fellowship awarded to Dr Eder Zavala: “Developing a mathematical and computational framework for digital endocrinology”. The work will build on hormonal time series data collected
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UKRI Future Leaders Fellowship awarded to Dr Eder Zavala: “Developing a mathematical and computational framework for digital endocrinology”. The work will build on hormonal time series data collected