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-party funded research Senckenberg is committed to diversity. We benefit from the different expertise, perspectives and personalities of our staff and welcome every application from qualified candidates
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of different types of populations. Work closely together with a PhD candidate on the same project and provide help with setting up simulations. Investigate the trend in genetic variance and genetic correlations
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enable us to test Risø HPP when it is connected to different electrical power grids, which we will emulate with the CGI. We are looking for a Postdoc who will be engaged in experimental research and model
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of Python language Eligibility Appointment to the position of postdoc requires that the applicant has a PhD or an international degree deemed equivalent to a PhD, within the subject of the position, completed
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and transient inverter modeling and different applications of the simulation. Selection will be based on qualifications, relevant experience, skills, and education. You should be highly self-motivated
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relevant field Proficiency in Python, and/or R statistical package. Proficiency in using LLM, model training, and Generative AI. Experience with supervised and unsupervised ML techniques Skill in collecting
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will evaluate potential biases among different measurement approaches —including thermochronology, cosmogenic nuclides, and suspended sediment records— and apply advanced statistical analyses and erosion
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methods, with demonstrated ability to implement causal identification strategies (difference-in-differences, instrumental variables, regression discontinuity, quasi-experimental designs). Proven experience
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and changes in the city on ridership (frequency, duration, location, etc). We will also look at different user segments, such as tourists and inhabitants and compare their ridership, etc. For this we
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB