AI Internship - Multi-label Classification

Springer Nature Artificial Intelligence

Technology is central to our ability to serve our communities and it has played a vital role in the success of Springer Nature. For instance, it enabled us, along with the rest of the academic publishing industry, to transition earlier than other content industries from print to digital and is behind our transition to open access.

AI has the potential to accelerate research progress further.

We believe AI has the potential to further accelerate discovery if supported by human oversight. We are therefore building on our experience and using technology and AI tools, all of which we are deploying alongside human intervention and with human oversight, to further help the research community. 

For example, with the help of AI we are curating data that would have taken humans years to collate and turn it into a book for academics to build upon.

AI also helps to promote equity by helping editors find the right peer reviewers from the vast scientific global network of academics faster and helps non-native English-speaking scientists to improve their science communication and reach new global audiences.

We are also using AI to build ever more sophisticated integrity checks to safeguard the scientific record.

Security and ethics remain essential to us, even in the era of AI ("human in the loop").

With all this activity, we have to put a strong focus on safety and ethics to help us mitigate risks and have an AI Ethics forum which has developed a set of principles to guide our activity.

Hierarchical Multi-Label Subject Prediction | SN AI

Imagine we have a paper about enhancing MRI images from the brain. This paper is both about medical imaging and deep learning. Each of these subjects is a branch of a broader set of subjects, namely, health science and computer science. In this internship, you will explore different ways to implement techniques for hierarchical multi-label subject prediction. We have something that does this today to use as your benchmark. Your task will be to implement and evaluate additional techniques found in the current research and propose and experiment with novel ideas. This internship will help you to develop more in the fields of deep learning, NLP, and multi-label classification -- all in an applied AI setting; side by side with engineers developing cutting-edge AI solutions every day.

What we are offering:

• A cool learning experience on real applied AI: software that internal and external scientific experts actually use

• Getting to know the "How-to" of software development in a professional context with awesome colleagues (e.g. scrum methods, peer feedback)

• Interesting challenges to further the field, and both your and our knowledge.

• A project that is foundational to real-life AI products

What we are expecting from you:

• A background in Software Engineering, Computer Science or AI

• You are proactive and independent and bring a lot of enthusiasm to your work! But most of all, you dare to ask questions and you are willing to learn – craving to understand how & why things work.

• You love building stuff, studying the literature to understand the latest and greatest, and applying that to a real-life problem.

• You have some knowledge of Pytorch, transformers, NLP models, and classifiers.

Practicalities:

• We are accepting applications until the 31st of December and will schedule interviews in the following 2 weeks

• The start date between mid-January and mid-February

• We offer a ±3 month internship

• You need to be available to perform an internship for at least 32 hours/week

Come join SN AI Lab!

SN AI Lab offers a fun, innovative, and dynamic entrepreneurial environment. We hire quirky interns who dare to take a stand and explore new directions, and many of us were interns ourselves! We empower our team to be self-leading, take initiative, and experiment. With us, you can build great AI software products and a rewarding career in tech.

....Plus lots of cake, fun team events, a stocked fridge, the typical pool table, and even a massage chair! (It seemed like a good idea at the time?)

Most importantly, we offer an environment for you to continuously learn with a fun, brilliant, international & diverse team, as we build great AI products to advance science.

If you think this sounds ‘gezellig’, we’d love to hear from you!

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