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integration of heterogeneous data sources. Experience with signal processing and statistical modeling of high-dimensional data. Strong programming skills in Python and relevant ML frameworks (PyTorch
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decision is made. Strong experience in deep generative models (e.g., diffusion models, VAEs, transformers) Programming proficiency in Python and PyTorch Interest in multimodal human communication and virtual
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working with large data sets. Strong programming skills (e.g. Python, PyTorch) Ability to work both independently and collaboratively in a multidisciplinary team. Preferred qualifications A doctoral degree
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. Assessment criteria It is particularly meritorious that the applicant has shown Programming expertise: Proficiency in Python, R, and/or workflow management systems (Nextflow, Snakemake) Bioinformatics
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and course development Extensive knowledge in system engineering Extensive knowledge in software engineering Extensive knowledge of Python Extensive knowledge in software development in a cloud
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ability to handle large and complex datasets, including preprocessing and integration. Strong programming skills (e.g., Python, R, MATLAB, or similar). Demonstrated ability to conduct independent research
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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, Computational Biology, Systems Biology, Computer Science, Biochemistry related to proteomics and mass spectrometry, or related field. Proven methodological and research expertise Strong Python and R skills
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Computational Biology, Bioinformatics, Systems Biology, or a related field Proven methodological and research expertise Strong programming skills (Python, R, Bash or equivalent) for omics data processing, QC
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. The required expertise includes raw UPLC-MS-collected data preprocessing with XCMS, MZmine or MSDIAL, normalization procedures, proficiency in R and/or Python for scripting and data analysis, metabolite ID via