37 scientific-programming Postdoctoral positions at Technical University of Denmark in Denmark
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remains not only scientifically rigorous but also directly relevant to real-world applications. Both postdocs will work on thermodynamic modeling of CCS systems, the development of equilibrium calculation
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genomic data from extinct and extant species, and machine learning, you will help develop a foundational tool for predicting extinction risk and advancing the use of genomics in conservation science. Job
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Job Description Are you driven by the potential of AI in medicine? Are you excited by the translational impact of bioengineering research and its potential to bridge fundamental science with real
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of microbial biogeochemistry Proficiency in scientific programming and data analysis using tools such as Python, R, MATLAB, or similar Excellent written and verbal communication skills in English
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in glaciology, Geodesy, Earth sciences, remote sensing, or a related field. Strong skills in data analysis, programming, and handling large geospatial datasets are essential. Experience with satellite
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, sequencing, cell cultivation). Plan, perform, and analyse yeast and immunological experiments independently, driving the project forward (e.g., cellular assays, immunoassays, flow cytometry, cell sorting
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dynamics of two- more persons’ data during social interaction (e.g., decision making, turn-taking dynamics, or eye-movements) strong programming skills in e.g., MATLAB or Python strong background in signal
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are looking for a candidate with a high degree of independence and a strong drive for scientific excellence. The position provides excellent opportunities for professional development and training towards
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit