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Program
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Field
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exciting research projects. Our work focuses on models and algorithms for supervised and unsupervised learning. We devise deep learning models, which find application in image-based science, including in
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learning algorithms constitutes a very promising research direction for energy-efficient and Edge AI applications: the goal here is to make these systems capable of learning per se, not just inference
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functional genomics (CRISPRi/a, Perturb seq, combinatorial screens), single cell and spatial omics, metabolomics, and immunopeptidomics. The successful candidate will pioneer assay-algorithm co design
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic
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algorithm development, numerical methods, or high-performance computing. Proficiency required in Python/C++ and scientific libraries (e.g., NumPy, SciPy). MATLAB is also desirable. Bonus: Familiarity with X
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. The incumbent will have the unique opportunity to work at the intersection of cutting-edge science and real-world application, developing groundbreaking algorithms and systems that mimic natural processes
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. For example, a proposal using neutral atoms to simulate a biological process, combining atomic physics, quantum algorithms, and biology, exemplifies the program’s interdisciplinary vision. Fellowship Funding
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11 Dec 2025 Job Information Organisation/Company Saarland University Research Field Mathematics » Algorithms Computer science » Other Researcher Profile Established Researcher (R3) Positions Postdoc
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be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives
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or more of the following areas: + Quantum computing and quantum algorithms + Solid-state physics, computational materials science, or quantum chemistry + Battery materials modeling Excellent