177 data-"https:"-"https:"-"https:"-"https:"-"University-of-Aberdeen" Postdoctoral positions in Denmark
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paths at DTU here . Further information Further information may be obtained from Professor Xenofon Fafoutis and Associate Professor Luca Pezzarossa . You can read more about ESE at www.compute.dtu.dk
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will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a shortlisting process. You
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with a background in either communication, journalism, political science, sociology, law, economics, or computational social science, as well as an interest in how AI transforms the media and information
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agreed upon with the relevant union. The period of employment is 2 years. You can read more about career paths at DTU here . Further information Further information may be obtained from Antonio Grimalt
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across career stages Starting date: April 1st 2026, or soon after Applicants seeking further information can contact: Professor Amelia-Elena Rotaru arotaruATbiology.sdu.dk . Who are we? The successful
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research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and
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metabolic data and correlate NMR readouts with physiological function. Preferred Qualifications: PhD in Bioengineering, Chemistry, Biophysics, or a related field. Extensive hands-on experience with organ-on-a
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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to the faculty’s departments. Consequently, your employment will as of that date be with a department. Contact information For further information, please contact: Professor Troels Skrydstrup, +45 28 99 21 32, ts
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will