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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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and one Postdoctoral position in the field of robot motion and control algorithms for soft material handling, starting September 2025. We are seeking highly qualified and motivated individuals with a
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algorithms into an existing framework, with a focus on efficiency, as well as creation and execution of relevant simulation pipelines: from real data to mathematical and clinically actionable results
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to publications and grant writing, and support the supervision of students and junior researchers in one the following research areas: Computational oncology AI drug discovery Statistical genetics, single-cell
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equivalent degree in agriculture, biology or any related field. You are an early career researcher not more than one year after your PhD and you have a proven track record and extensive experience with genetic
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
to decipher key regulators of human immune homeostasis (Ardy RC et al., Gastroenterology 2018; Wang L et al., Nat Genet 2021; Salzer E et al., Science Immunol 2020; Block et al., New Engl J Med 2023
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. The project’s overarching goal is the development of digital quantum algorithms for the simulation of non-abelian lattice gauge theories. We are looking for highly motivated individuals, with the desire
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on the influence of Alzheimer’s disease and aging on changes in cognitive functions in humans. The project combines cutting-edge technologies from genetics, proteomics and statistical modeling to understand