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, interdisciplinary teams, value diversity of thought, and enjoy the freedom to explore novel ideas. You communicate fluently in English, both orally and in writing. We Offer: Access to an international network
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with the land surface model to conduct regional simulations; Flux and concentration footprint modelling; Post-processing of eddy covariance data, gap filling and data analysis; Plan, coordinate and
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qualitative interview studies, surveys, register data, or experiments. The teaching of the department is very diverse across programs and areas and largely falls within the four research areas of the department
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Lomet, Research Engineer in AI at LIAD, CEA Saclay · Marianne Clausel (University of Lorraine), scientific lead of the national PEPR causali-t-ai program, · Myriam Tami, Associate Professor
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comprehensive benefits package to eligible employees, based on position, which includes: Medical, prescription drug, and dental coverage Paid vacation, holidays, and various leave programs Competitive retirement
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
for the formation of model membranes e.g. LB/LS deposition, RSE, etc. We Offer A friendly and respectful English-speaking working environment. Flexible working hours. Access to a world-class laboratory with state
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, education allowance, relocation support etc. Adequate research funds, and university’s supports to apply for national, provincial and municipal talent programs. Requirements: Ph.D. in Mathematics
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Morocco Application Deadline 19 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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learn mathematical modeling and quantitative analysis Ability to program in at least one of the following languages: Python, MATLAB, R or C Evidence of outreach, mentoring or community building. Required
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is necessary for career entry. Preferred Proficiency in UNIX shell, Python, or other programming languages is preferred. Experience handling large next-gen sequence datasets is preferred. A