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Research Associate (Artificial Intelligence/Computer Science/Optimization/Computational Linguistics)
implement simulation platforms and experimental pipelines for algorithm validation. Visualize simulation and experimental results to support decision-making and research findings. Contribute to: High-impact
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relevant research or working experience in LLM/VLM and AI decision-making algorithms for autonomous vehicles will be preferred. We regret to inform that only shortlisted candidates will be notified. Hiring
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like Genetic Algorithms (GA) and PID control, using MATLAB/Simulink. Experience with electrical and battery testing, soldering, and PCB design (e.g., Autodesk Eagle). Ability to work collaboratively in
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algorithms into the real development progress Preparing academic publications such as patent applications and research papers Contributing to quarterly and annual report writing and presenting Requirements
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. Ability to implement numerical and computational algorithms efficiently, with attention to reproducibility and software engineering best practices. Strong analytical and logical reasoning skills
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(Modbus, MQTT), and DER operations. Knowledge of cryptography, consensus algorithms, and security best practices. Prior experience in energy markets or financial settlement systems is highly desirable
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optimization models tailored to transportation and logistics contexts. Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to solve large-scale, real-world problems
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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Machine Learning algorithms Experience in conducting neuroimaging studies in educational contexts Experience in working with databases. Responsibilities Liaise with stakeholders (E.g. participating schools
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languages, logic and algorithms, formal methods, probability and measure theory. Strong publication record and familiarity with the existing literature and research in the field of statistical machine