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Mathematics, Data Science, or related fields. Strong background in Operations Research. Experience with industrial data processing, particularly in dynamic, real-time environments. Proficiency in machine
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. Experience with data prediction and classification techniques. Computer Skills: Good proficiency with optimization tools (CPLEX, SAP). Experience with data analysis software. Soft Skills: Analytical mindset
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, or CO₂ capture). Strong knowledge of adsorption isotherm models, mass transport mechanisms, and surface chemistry. Experience in synthesis, functionalization, and characterization of adsorbents
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designing, synthesizing, and characterizing highly catalytic active MOF composites for sensing using fluorescence-based sensing. Required qualifications: The candidates must have strong experience in MOF
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groups in the field Criteria of the candidate: To be considered for this role, you will ideally have: PhD in organic chemistry, polymer chemistry, colloids science or related field. Relevant experience and
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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. Qualifications: Ph.D. in Materials Science, Inorganic Chemistry, or a related field. Experience in the development of microporous materials. Strong expertise in material characterization techniques (e.g., FTIR
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in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a multidisciplinary team. Strong written and
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-element analytical techniques (PIXE, XRF, ICP-MS). Valorization of Industrial Waste: Experience in developing processes for treating and valorizing radioactive industrial waste. Cross-Functional Skills
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, or related fields, demonstrated by publications and/or fieldwork. Experience with qualitative research methods (e.g., ethnography, archival research, spatial analysis). Strong interest in interdisciplinary and