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. The candidates must submit the following documents: (a) a CV (specifying any relevant experience, along with a detailed description of previous accomplishments); (b) a cover letter highlighting the interest in
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of biological samples and experimental techniques. Experience in the collection, processing, storage and analysis of human biological samples, as well as in the application of molecular and cellular biology
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available biomarkers often fail to detect responders and non-responders. As a result, most cancer patients are not receiving the right treatment and often only experience the side effects of toxic (and
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related quantitative discipline. Strong programming skills in Python for scientific computing and reproducible research. (Optional) Experience in time-series analysis, with explicit attention to intraday
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on the project, project management and other general academic group activities. Requirements: Education: PhD in Chemistry with a masters in Nanotechnology preferred. Knowledge: Previous experience of having worked
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. Experience requirements Research experience in gravitational wave physics, astrophysics, astronomy, relativity, computational physics or related fields at postgraduate level is essential. Previous membership
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device-level properties of amorphous graphene nanoribbons and related structures. This will provide a bridge between atomistic material modelling and experimentally measurable device characteristics
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computing and reproducible research. (Optional) Experience in time-series analysis, with explicit attention to intraday temporal resolution. Background in network science, statistical physics and complex
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of realizations. It will be assessed: Good proficiency in written and oral English. Professional Experience: Extensive research on morphodynamic modeling of beaches at different time scales. In climates with waves
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. PhD in Microbiology, Microbiology-oriented Biomedicine, Biotechnology or a related discipline. Demonstrated hands-on experience with bacterial biofilms is essential: establishing and characterising in