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Computer Engineering or related areas; Knowledge of the development of automatic [deep] learning and information visualization applications; Experience in the use of algorithms and data analysis methods
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to develop basin-scale petrophysical models. Proven record of involvement in research projects relevant to oil and gas (O&G) and emerging energies. Ability to develop code/algorithms in Python or similar
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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the successful applicant will develop novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic
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manufacturing processes for processing using applied AI techniques. We anticipate the successful applicant will develop novel sensing approaches to combine with machine learning algorithms to solve real-world
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deep learning algorithms by leveraging LLMs and compare them with traditional methods; and 4) develop a set of tools on the project's website that can be used to evaluate lexical complexity, readability
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The University of Alabama, Department of Electrical and Computer Engineering | United States | 2 months ago
. Nathan Jeong shjeong@eng.ua.eduAdvanced Signal Processing and Machine Learning Algorithms for Autonomous Vehicles, Prof. Shunqiao Sun ssun21@eng.ua.eduTransportation Electrification and Power Distribution
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organisational goals. Stay at the forefront of AI advancements, translating breakthroughs into actionable solutions. Develop robust algorithms and tools to analyse structured and unstructured data and improve
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slicing, virtualization, SDN/MEC/NFV. Familiarity with AI/ML algorithms, tools, and basic workflows. Good publication record in scientific peer-reviewed journals Preferred Qualifications: Good knowledge
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of Alabama. Conducts research with Professor Moradkhani on a variety of projects. Leads the development of state-of-the art inverse modeling, optimization and assimilation algorithms and computational modeling