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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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position as research assistant for up to 6 months before starting the PhD program. The position is available from 1st September 2025 or soon thereafter. Application deadline is 20. June 2025. Research
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you like to contribute to an increased understanding of carbon cycle feedbacks in the climate system? Do you thrive in the dynamic blend of seagoing fieldwork, laboratory experiments and modelling? As a
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conferences Requirements: a university degree in the field of computer science, data science, computational modeling or related subjects in combination with civil engineering, transport engineering a strong
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modelling, starting as soon as possible. The position is funded for 36 months. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a part-time
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PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
also supervised by Prof. Dr. Jana Sillmann, who is co-leading the Research Unit for Sustainability and Climate Risks (FNK). This Research Unit is devoted to inter- and transdisciplinary research and
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technological solutions for the recycling of waste heat in specific food industry settings, using computational fluid dynamics modelling, lab experiments and field work To disseminate finding in high impact
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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dynamic and international research environment. Our research facilities include top-notch optics laboratories and access to a world-class cleanroom. Principal supervisor is Prof. Albert Schliesser (email
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underwater communications is necessary. Conventional approaches in underwater communications only develop fixed models based on human knowledge or understanding which cannot fully cover the highly dynamic and