Senior AI researcher

Research at the TransferLab is unconventional in its nature and breadth. Join us and help companies of all sizes by surveying, distilling, testing and communicating the latest in ML. Develop your own ideas on how best to improve the quality of ML applications and products, and publish in ways accessible and useful to everyone.

The appliedAI Institute advances Europe by creating and disseminating expertise in Artificial Intelligence. We are Europe’s largest initiative for the application of cutting-edge trustworthy AI, leveraging Europe’s innovative power through education, research, and publications. We aim to be a fully transparent, open-source organisation, where everyone is invited to participate, discuss, and to engage with AI. As a non-profit, we create visions for Europe as a society, for us in a world of climate change and for our economy in the age of AI. We want to contribute to sustainable wealth through technology, to shape a world we want to live in.

The TransferLab aims to identify, test and disseminate established and emerging techniques in machine learning at multiple difficulty and novelty levels in order to provide practitioners and businesses with the best tools for their applications. We constantly survey multiple fields in ML, challenging and testing statements in the literature with the goal of distilling useful knowledge for the industry in the form of trainings, in-depth reviews, software playbooks, showcase applications and blog posts, but also fund and conduct novel research advancing the application of AI in industry.

Position overview

As a researcher you will participate in our research efforts in one of our areas of interest, helping the TransferLab in its mission of identifying, testing and communicating recent results in ML of importance for practitioners. This entails constantly keeping an eye open for ideas that you think will play a leading role in the future, but also developing an agenda for applied research and publishing your results. Senior researchers usually end up leading a team and are expected to come up with, develop and manage their own projects, so experience as a leader is a benefit.

You will match your research to the needs of ML practitioners across broad domains. In addition, you will supervise and collaborate on the implementation of papers, benchmarks and courses. You will be responsible for selecting topics of relevance and ensuring that the claims in the literature are justified. Beyond this you will work on surveys of and tutorials on recent advances at the intersection of your expertise and our areas of interest. In doing this, you will contribute to existing open source projects or start new ones.

Your profile

We are looking for someone who knows machine learning and statistics both from the theoretical and applied perspectives. You should be able to understand recent developments and combine them with your own ideas, while being aware of and open about that which you don’t know. You will summarise papers, extend and write about methods, implement high quality, maintainable code, perform and interpret experiments, communicate your results, and thereby make a significant impact both on researchers and practitioners.

We found that people who can do this usually fit the following profile:

  • A solid mathematical background.
  • Research or significant industry experience and the ability to design and conduct your own research agenda.
  • Thorough understanding of essential statistics and machine learning concepts.
  • Proficiency in python. Experience with other programming languages would be beneficial.
  • In-depth knowledge of one particular domain in ML / data science / statistics. From Bayesian graphical models and causal inference to model interpretability or meta-learning for neural networks, you tell us about it and your research goals.
  • Team player with a willingness to learn new things.
  • Fluent English.

It would be advantageous to have:

  • Experience in writing on technical topics for a general audience (e.g. blog posts, magazine articles).
  • A Ph.D. in STEM, preferably Machine Learning, Mathematics, Statistics, Computer Science, or Physics.
  • Experience with standard software development practices and tools like version control, CI/CD, DevOps, ticketing systems and agile methodologies.
  • Experience contributing to open source projects.
  • An understanding of how complex professional software projects are run.
  • Experience with ETL pipelines, data cleaning, SQL / NoSQL databases.
  • Conversational German.

What we offer

  • Possibility to work on cutting edge topics and publish papers and code.
  • Possibility of remote work.
  • Extended budget for attending conferences and buying books.
  • A highly motivated team and dynamic environment, full of people who want to and can make an impact on Europe’s AI landscape.
  • A multilingual and multinational team of researchers, engineers, educational experts and strategists.