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adapted to the interests and strengths of the chosen applicant. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall
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scans. Experience with age-depth modelling (c14 dates, stratigraphic correlation). Experience with Python or similar programming language. Documented very good oral and written proficiency in English
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, you should: Have a PhD in some area of nucleic acid research preferably with bioinformatic or computational focus. Have expert knowledge in working with and developing bioinformatics tools in Python
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expert knowledge in working with and developing bioinformatics tools in Python, Julia, R or C++. Have extensive experience with NGS data analysis. Have experience in sample preparation for and sequencing
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skills with considerable experience with programming with python. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc. Experience
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programming skills, for example in Python (and/or R), and experience with relevant ML libraries (e.g. PyTorch, TensorFlow or similar). Experience with software/tool development for research, including good
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/or statistical modelling, demonstrated through thesis work and/or scientific publications. Solid programming skills, for example in Python (and/or R), and experience with relevant ML libraries (e.g
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essential: A high degree of independence Ability to construct/maintain and use complex experimental setups Proficiency in “big” data analysis (using MATLAB or Python), or Candidates with demonstrated
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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proficiency in English. Documented experience in CFD and numerical modeling, preferably with OpenFOAM, Nek5000, or LBM. Strong programming skills (C++, Python, or similar). Ability to work independently and