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: Algebraic geometry and number theory Area 3: Stochastics and mathematical finance Area 4: Discrete mathematics and optimization Area 5: Discrete geometry Area 6: Numerical mathematics Area 7: Applied analysis
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. Simulations will be run using existing simulation packages which will need to be extended by the prospective candidate. Analysis tools will be written by the candidate in C/C++. The required supercomputer
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with
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regulation, RNA biology, protein biochemistry, stem cells, bioinformatics, sequence analysis, mathematics, statistics, molecular evolution, or biophysics, and wish to work at the Max Planck Institute
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Several PhD positions (f/m/d) in International Research Training Group (iRTG) limits2vision Full PhD
support, mentoring and career development. A key component in our program are student secondments at the respective partner institute. After successful completion of the PhD, the trainee will obtain a
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perform a risk analysis of the resulting model outputs Present your scientific results at conferences, workshops, and seminars, and publish the work in peer‑reviewed journals Collaborate with project
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field • Is fluent in English • Is interested in finding innovative, creative solutions • Has good programming/data analysis skills • Is experienced or at least strongly interested in one
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software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new code via
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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within the Institute of Theoretical Computer Science at TU Dresden. The main research area is the design and analysis of algorithms and data structures, with possible focus areas including randomized