AI Internship project on search suggestions

Project on search suggestions, query expansion

4-6 months, starting in September 2018
Email before June 20

  • Are you a student in Artificial Intelligence or Data Science?
  • Are you looking for a research project where your work actually gets implemented in real life and in production?
  • Are you comfortable programming (i.e. in Python)?
  • Would you like to experience how it is to work at a mature startup which already exists for 4 years?

Then pay attention :)

We are currently offering an internship Artificial Intelligence / Data Science at our EdTech Startup I Hate Statistics, located in Amsterdam.

The challenges this internship is centered around are Search and relevant Suggestions (query expansion) for teachers. Read more on the challenge below.

What we can offer you

  • A place where you can learn a lot! We have already mentored three other AI/Data Science students with research projects.
  • A dedicated supervisor for weekly conversations and help when you need it.
  • Find out what is like working in a mature startup.
  • A young, fun and enthusiastic team
  • Your own research project, which is scientifically novel and interesting and practically useful at the same time
  • If you want: be part of the implementation of the project in production.
  • You will contributing to making available free learning materials for people all around the world
  • A monthly internship fee of 350,-
  • Free lunch :)

I Hate Statistics

We are I Hate Statistics and our mission is to make data and statistics understandable and accessible to all. We believe that everyone can learn statistics when you use clear visuals, humor and a lot of practice. :) That is why we have developed an online program that students at universities are using to learn statistics and math. By now we have supported 10.000 students in learning statistics and math.

You’ll be working in a small and motivated team of around 5-7 people, where everybody is prepared to work hard to reach our goals. We do not believe in a strict hierarchy. Instead, we try to help each other as much as possible in tackling the challenges that we come across during our work. Besides the work, there is plenty of room to relax as well. We believe in working hard but not too long, play some table tennis everyday after lunch and organise fun drinks every now and then. We also lunch everyday with the team. Here our semi-colleagues from the University of the Netherlands join in with whom we share our office in the Houthavens in Amsterdam.

We are happy, because students love the things we build and explain:

“I’m now doing the course Statistics I for the second time. Last year we had very little practice material. But with your program practice has become easy. It works very well and offers great explanations. I’m really happy to be using your website!” Love, Tessa

Interested what our program looks like? Take a look here.

Social Enterprise

But we do more: we develop interactive explainers on statistics that are being used by journalists and their readers. For example: Peil Je Wijzer, and interactive DIY explanation about polls and sampling error. Find the explainer here (in Dutch) Peil Je Wijzer in De Correspondent and in the NRC and here (in English).


Want to contribute to better statistics and math education for all? Scroll down and get an impression of our team as well!

The challenge: Suggestions for Search and Tagging

Our mission is to help students learn complex concepts faster and make that knowledge freely available for everyone. To achieve that, we work together with universities to support their statistics and math courses via our online practice platform.

To that end, we have developed a search engine for teachers. The idea: just like google, you type a subject you want exercises for, you get an ordered list of relevant results, you preview the exercises and add them to your personal online course.

Challenge A: teachers often type subjects that are too broad. Like “differentiation”. We want to help them, by giving suggestions: are you looking for “differentiation of elementary functions?” or “conceptual understanding of differentiation”. The first aim of your project is to provide these suggestions. This is comparable to query expansion.

Challenge B: when teachers have created their own exercises, they need to categorise it under the right topics. But our topics are fine-grained, so there are hundreds of topics. We want to help teachers by providing suggested topics. “Is this exercises about one of these topics?”

Scientifically novel: what makes this project scientifically interesting is the underlying architecture of our platform. We have implemented a ‘domain model’: a graph of all the hierarchical and prior knowledge relations between topics in math and statistics. Instead of using a generic algorithm to provide suggestions, you can make use of this knowledge graph. The question is: how to do this? That is the aim of this project.

Recap

  • We offer an internship position starting in september 2018, for 4-6 months.
  • Targeted towards Artificial Intelligence and Data Science master students
  • The project is about providing suggestions (query expansion), leveraging our domain graph
  • This will be your project. We will help you master it. You will learn a lot.
  • You’ll experience how it is working at a mature startup.
  • We are based at Rockstart, Amsterdam, Rigakade 10 at the Houthavens.

Interested?

Please send an email before june 20, 2018 to jobs@ihatestatistics.com with a short motivation and your experience.

Hope to hear from you!
Best,
I Hate Statistics :)