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and optimization of algorithms for these problems, as well as proofs on theoretical complexity bounds. Common tasks include: Developing ideas for improving existent or creating novel algorithms Coding
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. Proficiency in at least one of the following areas is required: Numerical methods for large-scale, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming
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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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