DATA SCIENTIST TRAINEESHIP OPPORTUNITY (ERASMUS+ CANDIDATES ONLY)

Data Scientist Traineeship Opportunity (Erasmus+ Candidates Only) Engineering and/or Technology, Mathematics and/or Informatics, Natural Sciences This is a Digital Opportunities Traineeship (DOT). If you want to apply for this internship, please remember that you have to be a student or recently graduated based in one of the 33 Programme Countries participating in Erasmus+ or the Horizon 2020 Associated Countries. Before applying for a Digital Opportunity Traineeship, we encourage you to check with your university if you are eligible for Erasmus+ traineeship. You can read more about DOT's in our information page. General Information Duration: 6 months Commitment: Full-time Description We are seeking a highly skilled and autonomous Data Scientist trainee for a minimum 6-month engagement within the Plantiverse project. This role focuses on developing and optimizing data-driven models to support AI/ML-based agricultural systems. The candidate will work in a collaborative environment but must be capable of handling independent tasks with minimal supervision. Ideal Candidate Profile Educational Background: Enrolled in or recently graduated from a program in Data Science, Computer Science, Applied Mathematics, or a related quantitative field. Technical Skills: Strong proficiency in Python , R , or similar programming languages, with a focus on data analysis and machine learning applications. Experience with large datasets, statistical methods, and applying machine learning models. Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and libraries such as Scikit-learn. Practical experience in data preprocessing, feature engineering, and model deployment. Understanding of cloud platforms (e.g., AWS, Azure) for data processing and training. Language Requirement: A good command of English is essential for communication, collaboration, and documentation. Learning and Development: Demonstrated interest in applying data science to real-world agricultural challenges. Ability to independently develop, test, and refine predictive models. Collaboration and Communication: Excellent written and verbal communication skills to report findings and collaborate effectively with team members. Leadership potential to guide other trainees, if necessary. Daily Tasks: Develop and implement machine learning models to optimize resource management in agriculture (e.g., irrigation, pest control). Analyze sensor and satellite data to derive insights on plant health and environmental conditions. Collaborate with AI/ML teams to integrate predictive models into the Plantiverse platform. Regularly assess model performance and refine parameters for optimal accuracy. Document processes and findings to support the broader team and future project iterations. Additional Information: This traineeship offers the opportunity to lead the data-driven aspects of a pioneering plant-driven agricultural platform. It requires strong technical skills and independence in managing projects. Partial online participation is possible to accommodate academic needs. How to Apply: Candidates interested in applying for this competitive traineeship should submit their CV , Cover Letter , and indicate their period of interest . Applications must be titled: “ Data_Scientist_Name_Surname_ddmmyy_Country ” and sent to ... . Note: We are currently considering Erasmus+ candidates only . #J-18808-Ljbffr