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, neural interfaces, energy harvesting and storage, and optics. From AI modelling of materials and biological complexity to the design of multifunctional micro- and nano systems, we combine theory
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geological models (e.g. in Petrel) Experience in sedimentological mapping and willingness to work in the field Structured, independent way of working and strong analytical thinking Good knowledge of German and
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role areas are: Developing and applying advanced molecular thermodynamic theories and models for water and electrolyte systems relevant to energy, materials, environmental, and biological applications
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Assistant to support applied research at the intersection of healthcare, artificial intelligence, and data analysis The primary focus of this role will be large language model (LLMs) and other machine
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/splicing, as well as the development of enhancer activity lineage-tracing approaches in stem cell and/or mouse models. We are particularly interested in candidates with expertise in transcriptional
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student success by creating an optimum learning environment, responding to student needs, managing effective instructional activities, modeling employability skills, demonstrating professionalism
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. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS CASC. Qualifications Required Qualifications: A completed
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, life science and energy research with world-leading industrial research and development projects. The division of Condensed Matter and Materials Theory constructs models for and develops
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Appointment Term: Initially 1 year, renewable Appointment Start Date: Start date is negotiable. Group or Departmental Website: https://www.huttenhainlab.com/ (link is external) How to Submit Application
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emerging trends for use in course development. Knowledge of Shareable Content Object Reference Model (SCORM), and 508 Accessibility requirements to ensure compliance. Ability to communicate in writing in a