Thesis Internship - Autumn 2026 at TKH AI Technology

T

Thesis Internship - Autumn 2026

TKH AI Technology

Amsterdam, North Holland, Netherlands

On-Site

Entry

posted 38 days ago

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Vacancy Summary

Are you a master's student eager to conduct thesis research on real AI challenges? Join TKH AI and work on impactful projects while collaborating with experienced AI engineers and researchers.

Required skills

PYTHON

AI Tools

Growth

Optimization

Research Methodology

Artificial Intelligence (AI)

Communication Skills

Computer Science

Dutch

Retrieval-Augmented Generation (RAG)

Technology

Support

Version Control (Git)

infrastructure

AI Products

LLMs

Benchmarking

Access

Coding

Vision

Guidance

Interfaces

Make

Suite (Centric)

CAN

data

Prototyping

Forms

Large Language Models (LLM)

Grounding

JOIN

Are you a master's student looking to conduct your thesis research on real AI challenges? Do you want to base your graduation project on questions that make an impact in an organization actively building and deploying AI? We may have a place for you to do your thesis research with us at TKH AI.

Over Ons

TKH Group consists of technology companies focused on client-centric technology systems in high-growth markets. TKH AI Technology, the group’s AI hub, addresses AI challenges faced by around 60 companies across the group. In building AI products and running AI projects with/for our sister companies, we encounter many questions that are worth examining more closely from a research perspective; these form the starting point for thesis projects.

De Rol

As a graduation intern at TKH AI Technology, you will shape the direction of your research project together with our AI engineers and researchers, and then carry out the work as the basis for your master's thesis. We are looking for someone we can think with, so you will have people to spar with and draw on for support throughout. You will have the space to investigate a genuine problem in depth and develop findings that can take different forms — a working prototype, or knowledge and insight that others can build on. Possible research directions include (but are not limited to):

•

Cache-aware smart routing for LLMs

•

Adaptive long-term memory for RAG systems

•

Selective memory and context-focusing for LLM coding agents

•

Class discovery using vision-language models (VLMs)

•

Generative data augmentation for few-shot tasks

•

Designing and evaluating agentic skills and model optimization

•

Benchmarking LLM-Wiki for question answering

•

A hybrid semantic–visual interface for LLM interaction with graphical user interfaces

•

Trust, disclosure, and channel choice in AI-mediated workplace communication

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