(March 30, 2016) Post-doc Position in Machine Learning & Social Media @ MIT, in cooperation with Twitter:

Machine learning has recently enabled substantial progress towards AI. These developments have ignited a growth in concerns from the general public about AI and its potential impact in our daily lives. This attention on the role of intelligent machines motivates a research agenda towards more transparent, understandable, and trustworthy machine learning systems. In the long term, for sophisticated machine learning systems to have positive societal impact, it is necessary to develop:

• Transparent models that can not only produce predictions, but can also provide an explanation for their predictions.
• Understandable models that can converse, maintain a dialogue with humans and answer questions.
• Trustworthy models that can provide a meaningful measure of its confidence in the predictions they make.

Professors Iyad Rahwan and Deb Roy from the MIT Media Lab are seeking two motivated and talented candidates for postdocs dedicated to these research topics. The candidates will also be interacting directly with Ryan Adams and Hugo Larochelle from Twitter Cortex.

The candidates should have or be near the completion of a PhD, with a demonstrable record of strong publications in the field of machine learning and an interest in the human dimension of applied machine learning. The ideal candidate will have expertise in large scale applications of deep learning and/or Bayesian methods.

To apply, send your CV, the names and contact details of at least two references, as well as a letter of intent in which you motivate your interest in this position and provide a brief description of research ideas you'd like to explore during your postdoc.

Application packages must be submitted to: ml-postdoc@media.mit.edu

(February 1, 2016) Four Post-doc Positions in Data Science, AI & Society @ MIT:

The Scalable Cooperation group, directed by Iyad Rahwan at the MIT Media Lab has 4 openings for post-doctoral associates to work on topics related to Data Science, Artificial Intelligence and Society.

For the first time in history, we have the ability to amass massive amounts of data about human behavior. Algorithms also mediate much of our social and economic interactions, combining big data with machine learning and AI techniques to serve us news, find us dates, recommend us products, and find us jobs. How can we design these social systems in a way that reflects our values, laws, social norms and ethics? In other words: how can we build tools for programming, debugging, and evaluating the emerging "algorithmic social contract" between humans?

Current areas of interest include psychological studies and computational models of machine ethics, bounds on computational privacy, computational models of fairness, reinforcement learning algorithms for human-machine cooperation, and algorithm-mediated collective intelligence and social media.

• a CV,
• a link to the candidates professional webpage,
• a 200 word research statement,
• two publications

Evaluation will begin on 15 Feb.