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background in trace element dynamics, soil–plant interactions, or environmental biogeochemistry. Experience in experimental design, data analysis, and scientific writing Added value: expertise in microbial
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broad and may include (but is not limited to): Machine learning for molecular and reaction property prediction AI-based reaction modeling and retrosynthetic analysis Data-driven approaches to spectroscopy
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systems that fuse multi-modal remote sensing, soil and phenology data to enable crop classification and precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded
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methods, instruments and perform data acquisition related to the project. Write proposals, reports, scientific articles and Patent proposals related to the project. Candidate Profile Strong proficiency in
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techniques and methodologies for cell analysis Analyze interpret complex biological data Publish scientific results in peer-reviewed journals Present research results at national scientific meetings Have a
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attitude and ability to work both in a team and independently. Strong written and verbal communication skills, with a record of peer-reviewed publications. Proficiency with statistical analysis and data
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letter (maximum 1 page) explaining the motivation for the position Contact information of 3 references (Applicants are assumed to have obtained their references’ consent to be contacted for this matter
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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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students or supervising research projects. Expertise in laboratory management, experimental design, and analysis in biotechnology contexts. Proficiency in relevant software tools for research, data analysis
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. Proficiency in relevant software tools for research, data analysis, and teaching (e.g., MATLAB, Python…). Strong problem-solving and critical-thinking skills. Ability to work in a multidisciplinary team and