Research Assistant In Simulation And Data Analysis For Agricultural Machinery
Research Assistant in Simulation and Data Analysis for Agricultural Machinery The group of agricultural mechanization of the Alma Mater Studiorum - University of Bologna is actively developing innovative, data-driven approaches for next-generation agricultural machinery, including agricultural robots and hybrid or electric machines.
Our research focuses on new machine scheduling methods to support carbon-neutral agriculture.
A key element of our approach is the adoption of simulation tools that allow for the evaluation of these technologies in a virtual environment before their implementation in real-world systems.
We are seeking a highly motivated research assistant to support this ambitious initiative.
The selected candidate will have the opportunity to work with cutting-edge hardware and software agricultural technologies, such as CANBUS, ISOBUS, GNSS, MatLab, etc.
They will be part of a dynamic, young research team and engage with a network of professionals, including industry leaders in agricultural machinery production.
The position offers a diverse work environment, combining desk-based research with hands-on field experiments involving large tractors.
Project Responsibilities: Data Analysis: Processing real-world data from over 30 tractors equipped with CANBUS technology, extracting key performance indicators (KPIs) relevant to stakeholders.
Simulation Modeling: Developing discrete event simulations (e. g. , in Matlab Stateflow) to replicate real-world farming scenarios using collected data.
Technology Evaluation: Assessing the economic, performance, and sustainability benefits of different agricultural technologies.
Candidate requirements: Proficiency in programming and modeling software such as Matlab or Python, with expertise in Stateflow, Statistics, and Machine Learning Toolbox.
Experience with data acquisition systems.
Knowledge of data analysis and optimization techniques.
Interest in conducting field experiments with agricultural machinery.
A master's degree in electrical engineering, computer science, mechanical engineering, physics, or mathematics.
A proactive attitude, eagerness to learn, and ability to tackle new challenges.
Seniority level Internship
Employment type Full-time
Industries Higher Education
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