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include: -PhD (or equivalent terminal degree) in relevant discipline, in biological sciences, microbiology, chemical engineering, biomedical engineering, or mechanical engineering -Experience with funded
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for linking basic and applied research, located in central Tuebingen The opportunity to establish your own junior research group, including a newly created PhD position (75% E13 TV-L). The team will also
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dynamics, Numerical Modeling, Scientific Computing, Applied Mathematics, Computational Chemistry). Experience in reactive transport modelling and strong background in reactive transport processes. Experience
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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://mediatum.ub.tum.de/doc/1696192/aab7jokzk7x4paq7m2y9pa2p6.Wetzlinger-2022-NAHS.pdf Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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to disseminate research results QUALIFICATIONS Applicants must have (or be about to receive) a PhD in physics, biophysics, systems biology, applied mathematics, bioengineering, chemistry, chemical engineering, or
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, mathematics, and innovation. Candidates must hold (or be close to completing) a Ph.D. in Applied Mathematics, Electrical or Mechanical Engineering, Physics and Applied Physics or a related field. Working in a
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biological systems, also in collaboration with other researchers and companies. Your profile Applicants should hold a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Physics
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degree and PhD degree in meteorology, oceanography, physics or mathematics, with a strong interest in the application of statistical and data analysis methods excellent knowledge in UNIX/Linux and Unix