The Information Management unit powers the ML6 teams with effective information. In order to this, we develop a series of internal tools (e.g. dashboards, applications, etc). We offer you an opportunity to work hands-on on applications, be it backend and/or frontend. We are looking for candidates that have worked with mainstream backend (preference: Python) and/or frontend languages (preference: React).

Potential topic: Insights Hub.
One of the tools from information management is the insights hub. The insights hub is web based tool to surf the internal knowledge graph, which in its turn gets data from our data lake.

LLMs like GPT promise to fundamentally change knowledge work. Many challenges remain, however, related to alignment, security, truthfulness, bias, performance, latency, cost and others. Work on one of these problems and help move forward the field towards truly useful, robust and measurable large language model applications!

Potential topics include:

1. Follow-up on the Product Innovation demo - building interactive product ideas (genAI agents and prompt engineering), 

2. Automated Content Research supported by LLM agents

3. NLP for modelling and identifying trending topics over time

4. Talk to your documents - leveraging generative AI for extracting insights from your documents

5. Leveraging multimodal LLMs for automated visual feedback

6. Generate your graph-database - using LLMs for automated knowledge graph building from documents

7. Instruction-based visual editing - tell your model how to change an image

Image generation models like Stable Diffusion are revolutionizing the creative industries and beyond by sharply increasing the reach and productivity of designers and allowing lay people to create prototypes in minutes. Techniques like Dreambooth and ControlNet further allow for the guidance of generative models in clever ways. Help us push the boundaries of AI image generation by researching new ways of guiding image generation and develop domain-specific use cases. 

Potential topics include Stacking multiple Lora's for concept-aware content generation, Generation of Coherent Storybook from Plain Text Story using Diffusion Models and Exploring the SOTA 3D capabilities. 

This domain focuses on using AI in the context of Industry 4.0. Think about digital twins, predictive maintenance, root cause analysis, process optimisation, process steering. We also see value for use cases where labeling data is expensive or difficult to do, which we tackle by using segment anything model, active learning or surrogate models. 

Potential topics include translating sign language in real life using an Apple Vision Pro.

Biology is intrinsically complex and diverse. Despite, decades of research, nature still holds many secrets. Today, there is an opportunity for AI to support the experts: mapping experiment input and output over very complex biological functions. 

Potential topics include Drug Discovery and Omics analysis.

AI can optimize resource management, enhance grid efficiency, and accelerate the transition to clean energy. This intersection holds the key to a sustainable and greener future, making it a crucial avenue for innovation and progress.

Potential internship topics within the energy domain include open-data forecasts analysis and refinement, balancing the net with AI, forecast energy trading, optimising (home) energy usage towards sustainability (using open data) and helping energy consumers with making educated decisions.

Operations is a term subsuming DevOps and MLOps. DevOps refers to a set of standards, practices and tooling that enable fast/high quality delivery and continuous improvements. MLOps extends DevOps to ML systems, which come with a set of challenges related to the training, deployment, monitoring and tracking of models.

For some of our most frequently solved challenges we offer hybrid solutions. These projects are based on a shared codebase and internships are centered on extending the shared codebase based on latest technical developments. Applications range from process steering in manufacturing to computer vision diagnostics and entity recognition in legal documents. 

Potential topics are domain adaptation for pose estimation in manufacturing, few-shot visual prompting on edge hardware and PLC standard package. 

We are looking for curious and ambitious Business Development interns to support the Business Development team in establishing ML6’s presence in the Belgian/Dutch/German market. As a consultancy company at the forefront of AI innovation, this hands-on project will provide you with the opportunity to work on key tasks that will shape the market positioning and introduction of our AI-driven solutions and services. You will also explore cutting-edge marketing techniques to promote complex AI solutions to a broad audience.

Generative AI has rapidly transformed the technology landscape. However, along with its potential, it raises significant ethical concerns that demand careful exploration. These ethical risks span across issues such as bias and misinformation. A research internship centred on 'How to tackle the ethical risks of Generative AI?' would involve a thorough investigation of these risks, drawing on existing academic papers, industry reports, and case studies, with the goal of producing an insightful deliverable in the form of a blog post, whitepaper, or ethical framework.