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scientific computing environment (e.g. Python, MATLAB, Modelica); experience with geothermal or reservoir modelling tools is an advantage. We regret to inform that only shortlisted candidates will be notified
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Research Associate (Artificial Intelligence/Computer Science/Optimization/Computational Linguistics)
solutions Requirements: Master’s degree in Artificial Intelligence, Computer Science, Optimization, Computational Linguistics, or a related field. Strong foundations in multi-agent systems, NLP and python
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models, and foundation models Strong programming skills in Python and deep learning frameworks such as PyTorch Experience with large-scale experiments, model optimization, and performance analysis
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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students and working effectively in a team-based research environment Proficiency in common computational chemistry software and coding techniques e.g. Gaussian/Amber/Schrödinger/python/bash For more
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Proficiency in python for machine learning Competent in soft skills / general personality traits e.g. information visualization, interaction design We regret to inform you that only shortlisted candidates will
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network modelling highly preferred Experience in optimal power flow and/or state monitoring/statement Proficient in MATLAB, Python, or similar programming languages Experience in power systems simulation
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applications Proven experience leading or managing complex software platforms Good written and oral communication skills Technical skills Backend development using Elixir, Erlang, Python, or similar languages
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buses, communication networks, power engineering simulations, embedded C and Python programming. Competent in soft skills / general personality traits e.g. information visualization, interaction design
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with neuroimaging software (e.g., SPM, AFNI, FSL). Familiar with coding (e.g., in R, MATLAB, Python). Experience with research project management. Experience with supervising research staff and students