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Imperial College London

PhD positions at Imperial College London on data privacy and security (fully funded, deadline: Nov 15, 2021)

Our Computational Privacy Group at Imperial College London is offering fully funded PhD positions for 2021.

Topics of current interests include re-identification of individuals in large-scale behavioral datasets; statistical or machine learning-based attacks against privacy-preserving data systems or aggregates, privacy of machine learning models, as well as privacy engineering solutions such as differential privacy and query-based systems.

We are looking for candidates who love exploring new ideas, are willing to collaborate with others, and would like to generate impact through their research. Our research has been published in top journals and conferences such as Science, Nature Communications, or Usenix Security and has been widely cited in the press and public policy documents.

For full details, please consult https://cpg.doc.ic.ac.uk/openings/

Deadline: Oct 15th (prefered) or Nov 15th, 2021

Recommended prerequisites. MSc or MEng (4y BEng will be considered) in computer science, statistics, mathematics, or a related field. Experience in statistics and/or machine learning is a plus.

We encourage all qualified candidates to apply, in particular women, disabled, BAME, and LGBTQIA+ candidates.

About Imperial: Imperial College London, ranked 9th globally, is one of the top universities in the world. A full-time PhD at the South Kensington Campus takes 3-4

years, is fully funded and usually starts in October.

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AI Competition -BNP Parisbas

I contact you on behalf of École Polytechnique and BNP Paribas to announce to you the Generative Modelling GenHack Data Science Challenge 

The GenHack challengeis an exciting opportunity for your students to improve and apply their skills in a challenging, international environment on a real-world industrial problem.

The task

This is an unsupervised learning problem: Given real data from stock market indexes that will act as a train dataset, the task is to develop a generative model that simulates synthetic stock market indexes.

🗓 When?

The competition will begin the 25th of October and will end the 22nd of November.

🤖 How?

  • Kick-off presentation on the 15th of October with the different stakeholders from BNP Paribas and Ecole Polytechnique.
  • Teams of 3-5 students (ideally from different universities and different countries).
  • Mentoring from academic experts and senior Data Scientists from BNP Paribas.

🏆 The Prize?

  • Present in front of the jury of École Polytechnique and BNP Paribas
  • Monetary prizes, unveiled at a later date
  • Discover BNP Paribas’s “métiers” during an exclusive event

💎 The Sponsors?

  • École Polytechnique, with the chaire ‘Stress Test: RISK Management and Financial Steering’ led by Professor Emmanuel Gobet.
  • BNP Paribas, with Léa Deleris, Head of RISK Artificial Intelligence Research, and Antoine Bezat, Head of Stress Testing Methodologies and Models

Is this something that you think your students could be interested in?

If so, please download from here the competition poster that you can share by email or hang on the wall of your Master’s classrooms.

Here is the platform where the students can sign up: competitions.outcoder.ai/competitions/genm

Enrollment deadline is the 15 October 2021 at midnight Paris time (GMT+2). Teams can be created after enrolling.

Please tell us if this is something you think your students will be interested in and if you have any questions.

 Kind regards,

On behalf of the organizing committee

Luca Zanna, Outcoder.ai