R&D Trainee System Tester (AI Driven Software) M/F

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R&D Trainee System Tester (AI Driven Software) M/F

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Vacancy details

General information

Reference

2026-660

Position description

Job title

R&D Trainee System Tester (AI Driven Software) M/F

Profile

Within Customized Energy Systems which is part of the Exide Technologies group we have our core software which controls the Battery Energy Storage System (BESS).

Various peripherals are used to read the signals required for control or to cool / heat the batteries or monitor the safety systems.

Battery Energy Storage Systems (BESS) are increasingly used to support the energy transition, grid stability, and industrial electrification. Beyond basic monitoring, leading BESS vendors are now integrating AI-driven analytics and digital twins to optimize battery lifetime, detect degradation and imbalance early, and reduce operation & maintenance (O&M) costs.

Within our organization, BESS systems already generate high-resolution operational data. This data is logged locally on each system and partially transferred to the cloud for visualization. The next step is to transform this data into actionable intelligence, using AI models and a digital-twin approach.

Assignment Description

During this project, you will work at the intersection of energy systems, data analytics, and applied AI. The assignment is modular and can be scaled to your level (HBO /MSc).

Key activities may include

• Analysing existing BESS operational data (voltages, currents, temperature,

SOC, events).

• Defining KPIs and health indicators related to capacity loss and imbalance.
• Developing and validating AI models for capacity estimation and imbalance

detection.

• Building a digital-twin prototype that allows scenario or “what-if” analysis (e.g.

impact of imbalance, aging, or operating conditions).

• Translating results into clear outputs for service and O&M use cases.
• Designing or advising on a cloud-based infrastructure for AI analytics (data

flow, model execution, outputs).

The project is exploratory and research-oriented, but strongly connected to real

systems in operation

HBO or MSc student in Electrical Engineering, Energy Systems, Data Science,

AI, or Embedded/Industrial Software.

• Interest in battery systems, energy storage, or smart energy solutions.
• Experience with or interest in Python, data analysis, and basic machine

learning.

• Analytical mindset, able to structure complex technical problems.
• Comfortable working with real operational data

We offer

A technically challenging project at the forefront of AI and energy storage.

• Direct exposure to real BESS systems and operational challenges.
• Guidance from experienced R&D engineers.
• Flexibility in project depth depending on HBO or MSc level.
• A project well suited for thesis, internship, or graduation assignment.

Location: Helmond (hybrid possible)

Duration: In line with HBO / MSc internship requirement

Position location

Job location

Netherlands, ATEPS

Location

Helm

Candidate criteria

Minimum level of education required

6- Others

Minimum level of experience required

Less than 2 years

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