WO Stage - PQI Slab Logistics

Tata Steel IJmuiden; Netherlands; On-site; EUR 5,600 - 7,800; Full time

Benefits offered by this job

Stagevergoeding

Begeleiding door onderzoekers

Interne training

Job summary

Tata Steel Nederland zoekt een MSc-stagiair voor de afdeling Product Quality & Innovation (PQI). Je ontwikkelt en evalueert AI-gebaseerde decision-support voor het toewijzen van hete kamers in slab-logistiek, met focus op energiebesparing en minder crane‑bewegingen.

Je werkt aan een hybride AI-benadering, bouwt voort op bestaande heuristieken en simulatiemodellen, en levert een compact prototype met evaluaties op basis van beschikbare data.

Qualifications

• Student in MSc-programma (Computer Science, AI, Data Science of related field).
• Sterke Python-programmeerkwaliteiten en база kennis ML.
• Interesse in optimalisatie, logistiek of simulatie.
• In staat zelfstandig een technisch probleem te structureren.

Responsibilities

• Ontwikkelen en evalueren van een AI-gebaseerde decision-support voor hete kamers in slab-logistiek.
• Onderzoeken van hybride AI-benaderingen en training van initiële beslissingsmodellen.
• Geven van demonstraties en evaluaties met behulp van simulaties en beschikbare data.
• Leveren van een compact prototype en documentatie.

Skills

Python programming

Machine learning

Optimization

Logistics

Simulation

Independent work

Problem structuring

Education

MSc in Computer Science

MSc in Artificial Intelligence

MSc in Data Science

Tools

PyTorch

Python

Simulation software

Job description

Dit ga jij doen

An average day…

You will work in the Product Quality & Innovation (PQI) Department, together with researchers from different technical backgrounds. Your work will focus on improving the use of hot rooms in slab logistics at Tata Steel Nederland. The goal is to support better allocation decisions that keep slabs hot for longer, while avoiding unnecessary crane operations and reshuffling.

You will build on an existing slab logistics model and previously developed heuristic approaches. Your main task will be to investigate how AI methods can support smarter hot-room allocation and help evaluate future logistics concepts.

What are you going to do?

Steel slabs lose thermal energy during storage and transport between production areas and the hot strip mill. Hot rooms can reduce this heat loss, but their value depends strongly on how they are used. Poor allocation may lead to unnecessary slab movements, extra crane operations, and limited operational acceptance.

In this internship, you will develop and evaluate an AI-based decision-support approach for hot-room allocation. The preferred direction is a hybrid AI method, where existing heuristic or meta-heuristic solutions are used to train an initial decision model, which may later be improved using reinforcement learning or related techniques.

The model should help answer questions such as:

• how to increase hot-room utilization without excessive crane movements;
• whether additional or mobile hot rooms provide operational value;
• whether heated hot rooms could further improve energy efficiency.

The work will be performed using simulation scenarios and available process/logistics data where possible. The result should be a compact prototype and evaluation showing how AI can support future energy-efficient slab logistics.

Dit bieden wij jou

• A 3- to 4-month MSc internship assignment.
• A monthly internship allowance.
• A challenging project at the interface of AI, logistics, and energy efficiency.
• Supervision from researchers and domain experts.
• The opportunity to contribute to Tata Steel Nederland's transition towards smarter and more sustainable steel production.

Herken jij jezelf?

This assignment is intended for an MSc student in Computer Science, Artificial Intelligence, Data Science, Operations Research, or a related field. Furthermore, you have:

• strong Python programming skills;
• knowledge of machine learning;
• interest in optimization, logistics, or simulation;
• ability to work independently and structure a technical problem clearly.

Experience with reinforcement learning, imitation learning, PyTorch, simulation models, or industrial scheduling is considered an advantage.

Jouw werkomgeving

What is your working environment?

You will work in an informal, research-oriented environment where practical impact and technical quality are both important. You will interact with researchers and operational experts to understand the logistics context and evaluate whether the developed AI approach is useful for real industrial decision‑making. The internship will be carried out mainly at our office, with the required equipment and support provided.

Tata Steel challenges you!

Tata Steel Nederland is working on major changes in steel production and energy use. Smarter logistics and better heat retention can contribute to reducing reheating demand, natural gas consumption, and CO2 emissions. Are you interested in applying AI to a real industrial sustainability challenge? Then this internship offers the opportunity to work on a concrete problem with both scientific and operational relevance.

Onze ambitie & diversiteit

Onze ambitie

Een groen, schoner en circulair staalbedrijf waar iedereen trots op is, dat is onze ambitie. We willen verbeteren hoe mensen over de hele wereld werken, leven en bewegen door middel van duurzaam staal. Om dit te laten slagen hebben we talenten nodig zoals jij. Maak jij samen met ons werk van de toekomst?

Diversiteit

Bij Tata Steel zijn wij ervan overtuigd dat diversiteit een grote bijdrage levert aan onze organisatie. Daarom streven wij constant naar een goede afspiegeling tussen de arbeidsmarkt en onze medewerkers.