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semiconductors. You should have experience working in a laboratory environment, along with basic programming and data analysis skills (Python, MATLAB, LabVIEW). High motivation, very good English or German skills
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programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in
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Experience in quantitative data analysis and in handling complex bodies of data in the use of at least one programming language (e. g. Python, Java ...) Language skills (CEFR-Level): English at least C1
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Python or similar. Experience with optics and/or reflectometry for X-rays and/or neutrons. Personal drive and self-motivated. Good communication skills in English, both written and spoken. Being able
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software as python packages Reporting findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data
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techniques e.g. laser and optical instrumentation; computational/numerical modelling programming skills e.g. Python, C++. Eligibility Open to both UK and International applicants, including EU applicants. How
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
, France, industries, etc). Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09879 Requirements Skills/Qualifications Good skills in Python (Pytorch). Ideally, prior experience with
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data processing, single-cell data processing, and Matlab, R, or Python, and scientific illustrations will be an advantage. Finally, the ideal applicant also has high proficiency in spoken and written
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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python
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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic