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. Richard Nickl and work in the project area 'Statistical aspects of non-linear inverse problems', which broadly addresses mathematical and foundational challenges in contemporary data science and the theory
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decision-support tool to incorporate biodiversity and land use. This data-driven tool provides diverse users with a manipulatable graphical interface to explore the impact of different drivers of change (e.g
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operating and interpreting data from analytical and characterization equipment, including: Universal Mechanical Testing Machine Scanning Electron Microscope (SEM) DTG thermal analyzer FT‑IR spectroscopy
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Postdoc in Decoding Biological Nitrification Inhibition (BNI) in Cereals: Integrating Metabolomic...
An ability to take initiative, develop, and manage research activities Proficient quantitative skills with data analysis and programming e.g. in R and python Documented experience in scientific writing and
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24 Feb 2026 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Biological sciences » Botany Environmental science » Ecology Biological sciences
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: Establish and develop experimental protocols and pipelines and implement data management compliance. Presentation of your work in various meetings (locally at the department, national and international
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An ability to take initiative, develop, and manage research activities Proficient quantitative skills with data analysis and programming e.g. in R and python Documented experience in scientific writing and
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needed for carrying out experiments, designing and running experiments, organising, analysing and interpreting data and sharing data with the wider team, writing manuscripts about key findings. They will
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communication skills, including the ability to write text that can be published, present data at conferences, and represent the research group at meetings. This full-time post is available immediately and is
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designing/programming experiments, recruiting/running participants, developing and using computational modeling approaches (Bayesian, RL, neural networks) to analyze behavioral and neuroimaging data