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Field
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assistantship. The ideal candidate will have a strong understanding of NLP, machine learning, and AI ethics, with proven skills in Python and frameworks like TensorFlow or PyTorch. Preference may be given
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literacy and basic programming skills (R, Python), or the willingness to develop these skills Analytical mindset, with a keen interest in advancing proteomic methodologies We offer Cutting-edge proteomic
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, Computational Biology, Systems Biology, or a related field Strong programming skills in R and/or Python Experience with single-cell or multi-omics data analysis Interest in cancer biology, particularly leukemia
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to participate in international meetings Experience with conducting and documenting scientific experiments as well as processing and analyzing data (Python, Origin, Excel) Good communication in English, knowledge
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and image analysis. Programming skills in Python and ImageJ are advantageous. Interest in interdisciplinary and international teamwork. Excellent written and spoken English. Our Offer: We work on the
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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and administration. Your profile: Completed Master's / Diploma degree in the field of Astrophysics Extensive programming knowledge (Python) Excellent command of written and spoken English (C1 level
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that provides a sufficient degree of background in computer science, artificial intelligence, mathematics and/or data science. Fluency in English and Python are required. Experience working with real-world
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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with coding, ideally in Python or MATLAB Funding support This studentship is open to Home students only. It is jointly supported by the Faculty of Engineering and industrial partners which is expected