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with statistical modeling (ideally Bayesian statistics) • Proficiency in Fortran, R, Python, Matlab, or ideally other common languages (e.g., C/C++) Strong computational skills Strong oral and written
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in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a multidisciplinary team. Strong written and
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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cochlear implants Investigations of how cognitive-linguistic factors, social environments, and auditory experiences shape individual differences in CI outcomes and speech communication in normal-hearing
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shapes (shovel, spade, keel, and round), thought to be adapted to different burrowing strategies. To study the skeletal adaptation, we will examine the chemical composition and nanostructure of skull
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shapes (shovel, spade, keel, and round), thought to be adapted to different burrowing strategies. To study the skeletal adaptation, we will examine the chemical composition and nanostructure of skull
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not have exceeded two years previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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production with an associated photon. • Technical skills in the use of columnar analysis approaches with python. Desired Qualifications • Experience with C++ programming. • Experience in developing
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biologist to decipher the genomic regulatory code controlling gene expression in plants. Within the ERC-funded multiCODE project, we aim to unravel how plants control gene expression across different tissues