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sampling, analytical methods such as GC-MS, LC-MS, or other relevant instrumentation. Experience in olfactory system research is highly desirable. Background in experimental design, data analysis
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methods. Programming languages, i.e. Python, Matlab, ... Level of experience evidenced by publications in peer-reviewed journals. Fluent in French and English. Experience of working as a member of a
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synthesis will involve wet chemistry and other well-established solid-state methods. Required qualifications: The candidate must hold a PhD degree in Materials Science, Materials Chemistry, Inorganic
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algebra algorithms, including sparse/dense linear systems solving and preconditioners. Scalable implementations of linear algebra methods targeting large-scale HPC systems. Optimization of linear algebra
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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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plant performance. Analyze experimental data using appropriate statistical methods and communicate findings through scientific publications. Work closely with researchers from other disciplines, such as
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systems including fault detection, diagnosis, and performance improvement methods. Mastery of dynamic reconfiguration approaches. Mastery of power converters. Mastery of software tools including MATLAB
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methods (e.g., ethnography, archival research, spatial analysis). Strong interest in interdisciplinary and Global South perspectives. Excellent writing and communication skills in English; proficiency in
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modeling applied to urban dynamics. Publications in scientific journals. Personal and Organizational Qualifications: Ability to develop innovative methods. Ambition for research excellence. Interest in
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Li-ion cathode materials using solid-state synthesis, sol-gel, co-precipitation, and hydrothermal methods. Structural and Chemical Characterization using: X-ray Powder Diffraction (XRD) and Rietveld