[Jobs] Research Internships at ByteDance AI Lab (Remote within Europe) - 2021 Start

Dell Zhang <000066bd11bd16e9-dmarc-request-fDUS8cNZx2jrfANEuwkQdg@public.gmane.org>
Newsgroups gmane.comp.information-retrieval.bcs-irsg
Message-ID <CAMbFHF_3-zgR7-zLi_oJp-jzLqzyd+gY9ZYrN_HdweodzjDZUw@mail.gmail.com>
Position: Research Intern
Location: Remote within Europe
Research Area: Responsible AI (Machine Learning Fairness etc.)


# Background

Founded in 2012, ByteDance is a technology company operating a range
of content platforms that inform, educate, entertain and inspire
people across languages, cultures and geographies. With a suite of
more than a dozen products, including TikTok, Douyin, Toutiao, Lark,
Helo and Resso, ByteDance now has a portfolio of applications
available in over 150 markets and 75 languages.

Our new MLF (Machine Learning Fairness) team based in the TikTok
London office is dedicated to building a technology center to provide
technical support for all ByteDance products from the perspectives of
Responsible AI. We are looking for PhD student interns who have solid
technical skills while being passionate about pursuing excellence in
machine learning fairness and related areas.

Please note that this role is to start immediately, not in 2022.

# Responsibilities

- Conduct research and development of technologies on machine learning
fairness and more generally AI ethics (including but not limited to
machine learning explainability, robustness, and privacy);
- Carry out design and analysis of ethical machine learning
algorithms, and apply them to recommendation, search, CV, NLP and
other products;
- Work closely with other researchers in the global MLF team;
- Publish research results in prestigious conferences and journals, or
file patents.

# Qualifications

- Currently in the process of obtaining a PhD degree in the relevant
field (including but not limited to machine learning, data mining,
information retrieval, natural language processing, computer vision,
and statistics)
- In-depth understanding of machine learning;
- Solid mathematical background and coding ability;
- Publications at top theoretical/applied machine learning conferences
 (e.g. ICML, NeurIPS, ICLR, SIGIR, WWW, WSDM, KDD, and FAccT) would be
a big plus.


To apply for this position, please visit:
https://careers.tiktok.com/position/7002681702675220766/detail

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