Graduation Project Reinforcement Learning for Logistic Optimization

Boskalis is currently looking for a student to start (February/March 2025 their graduation project with us. Logistic planning is a complex task involving numerous dependencies and a chain of events especially in the largescale projects that Boskalis conducts. Many projects share common challenges such as aligning our assets accounting for external dynamic factors and meeting the objectives desired by venture partners. Traditional planning methods involve heuristic calculations guided by experience or rules of thumb which are difficult to manage manually. MultiAgent Systems (MAS) and Reinforcement Learning (RL) are promising fields worth exploring as they have shown success in solving NPhard problems through simulation and verification.

The research project will require the student to conduct a literature review on developing such systems for our defined realworld projects. This will involve finding or building appropriate simulations to run these algorithms. Key design choices need to be made such as defining the elements of the RL agent(s) and their environment. With a variety of RL algorithms and frameworks available an educated choice must be made to address our specific problem effectively.

In this research you will

• Work with other data scientists and meet with multidisciplinary operational engineers to understand the challenge.
• Conduct literature research on MAS and RL and how they can be used for making schedules.
• Formulate the problem in a mathematical model.
• Develop efficient generic methods for making schedules for the chosen methods and demonstrate how they can be scaled up for future needs.
• Report your final findings demonstrating your design choices and reproducibility of results.

Your qualities

• You are doing a university masters degree in computer science AI mathematics or other related field.
• Affinity with Python and version controlling.
• Able to develop train and evaluate AI models using TensorFlow PyTorch Keras.
• Theoretical understanding of MAS and RL practical knowledge is not requested but pre.
• Proficiency in writing reports and findings and presenting results.
• It is preferred to be working at our office in Papendrecht 3 days a week.

Qualifications :

The resources that you will be able to use

• Receive supervision and support from data science experts from the Data Science & Engineering department.
• Gain access to necessary data and compute resources for training and deploying models (Databricks).
• Low threshold to plan meetings with people to gain a better understanding.
• Utilize wellestablished development facilities (Python source code control packaging).
• Access and review other developments that the Data Science & Engineering department are working on.

What you can expect

• Internship guidance: We offer you the opportunity to get the most out of your internship by giving you the right guidance.
• Warm welcome: You can count on a warm welcome so that you quickly feel at home at Boskalis.
• Salary and more: As an intern you will receive an internship allowance. In addition we offer a fun work environment with lots of challenges.
• A dynamic work environment: An internship where you can learn a lot from a leading company and where you will be part of a diverse team of experts.
• Young Boskalis: Are you younger than 36 Then join Young Boskalis! Monthly social and sporting activities ranging from pub quizzes yoga bootcamps and an annual sailboat race. Networking and knowledge sharing are also an important part of Young Boskalis.

Additional Information :

Want to know more  
Well be happy to answer your questions. Please get in touch with Tim Gouweleeuw (corporate recruiter) via  

Interested Please apply!

Disclaimer for recruitment and selection agencies 

We dont accept any unsolicited applications or CVs from recruitment and selection agencies. 

Remote Work :

No

Employment Type :

Fulltime