Microsoft Research NYC [ http://research.microsoft.com/newyork/ ] seeks 
outstanding applicants for 2-year postdoctoral researcher positions. We welcome 
applicants with a strong academic record in one of the following areas:

* Computational social science: http://research.microsoft.com/cssnyc
* Online experimental social science: http://research.microsoft.com/oess_nyc
* Algorithmic economics and market design: 
http://research.microsoft.com/algorithmic-economics/
* Machine learning: http://research.microsoft.com/mlnyc/

We will also consider applicants in other focus areas of the lab, including 
information retrieval, and behavioral & empirical economics. Additional 
information about these areas is included below. Please submit all application 
materials by January 11, 2013. Instructions are here: 
http://research.microsoft.com/en-us/jobs/fulltime/postdoc.aspx#NYC

----------

COMPUTATIONAL SOCIAL SCIENCE
http://research.microsoft.com/cssnyc

With an increasing amount of data on every aspect of our daily activities -- 
from what we buy, to where we travel, to who we know -- we are able to measure 
human behavior with precision largely thought impossible just a decade ago. 
Lying at the intersection of computer science, statistics and the social 
sciences, the emerging field of computational social science uses large-scale 
demographic, behavioral and network data to address longstanding questions in 
sociology, economics, politics, and beyond. We seek postdoc applicants with a 
diverse set of skills, including experience with large-scale data, scalable 
statistical and machine learning methods, and knowledge of a substantive social 
science field, such as sociology, economics, psychology, political science, or 
marketing.

ONLINE EXPERIMENTAL SOCIAL SCIENCE
http://research.microsoft.com/oess_nyc

Online experimental social science involves using the web, including 
crowdsourcing platforms such as Amazon's Mechanical Turk, to study human 
behavior in "virtual lab" environments.  Among other topics, virtual labs have 
been used to study the relationship  between financial incentives and 
performance, the honesty of online workers, advertising impact as a function of 
exposure time,  the implicit cost of "bad ads," the testing of graphical user 
interfaces eliciting probabilistic information and also the relationship 
between network structure and social dynamics, related to social phenomena such 
as cooperation, learning, and collective problem solving. We seek postdoc 
applicants with a diverse mix of skills, including awareness of the theoretical 
and experimental  social science literature, and experience with experimental 
design, as well as demonstrated statistical modeling and programming expertise. 
Specific experience running experiments on Amazon’s Mechanical Turk or related 
crowdsourcing websites, as well as managing virtual participant pools is also 
desirable, as is evidence of UI design ability.


ALGORITHMIC ECONOMICS AND MARKET DESIGN
http://research.microsoft.com/algorithmic-economics/

Market design, the engineering arm of economics, benefits from an understanding 
of computation: complexity, algorithms, engineering practice, and data. 
Conversely, computer science in a networked world benefits from a solid 
foundation in economics: incentives and game theory. Scientists with hybrid 
expertise are crucial as social systems of all types move to electronic 
platforms, as people increasingly rely on programmatic trading aids, as market 
designers rely more on equilibrium simulations, and as optimization and machine 
learning algorithms become part of the inner loop of social and economic 
mechanisms. We seek applicants who embody a diverse mix of skills, including a 
background in computer science (e.g., artificial intelligence or theory) or 
related field, and knowledge of the theoretical and experimental economics 
literature. Experience building prototype systems, and a comfort level with 
modern programming paradigms (e.g., web programming and map-reduce) are also 
desirable.


MACHINE LEARNING
http://research.microsoft.com/mlnyc/

Machine learning is the discipline of designing efficient algorithms for making 
accurate predictions and optimal decisions in the face of uncertainty. It 
combines tools and techniques from computer science, signal processing, 
statistics and optimization. Microsoft offers a unique opportunity to work with 
extremely diverse data sources, both big and small, while also offering a very 
stimulating environment for cutting-edge theoretical research. We seek postdoc 
applicants who have demonstrated ability to do independent research, have a 
strong publication record at top research venues and thrive in a 
multidisciplinary environment.
_______________________________________________
uai mailing list
uai@ENGR.ORST.EDU
https://secure.engr.oregonstate.edu/mailman/listinfo/uai

Reply via email to