geistlogistic

Mendeley is recruiting a Marie Curie Senior Research Fellow. Your primary responsibility will be to ensure that Mendeley’s research catalogue (i.e. collection of articles) is of high quality. Mendeley has crowdsourced the world’s largest research catalogue with over 50 million unique articles contributed by almost two million users over a period of four years. With your expert knowledge in data technologies and algorithms, you will take ownership of this catalogue, and work on innovative techniques for improving its quality. Your work should result in a cleaner, better structured and more scalable catalogue.

This position is part of the TEAM project (http://team-project.tugraz.at). You will spend 1 year in Mendeley’s London office before spending 1 year at TU Graz, the Knowledge Management Institute (http://kmi.tugraz.at/), Austria, collaborating with a top-class team. You will be passionate about working with large scale data collections and take pride in producing high quality data.

Description

Responsibilities

Ensure that the research catalogue is of high quality
Understand, maintain and help develop current crowdsourcing system
Disseminate results from your work both internally and externally

What you’ll be doing

Crowdsourcing a homogeneous catalogue from heterogeneous data sources, using modern data techniques
Identifying data sources, judging their appropriateness and working with data engineers to import them into the catalogue
Working with Data Engineers and Platform Team to make reliable/scalable systems
Working with Data Architect to ensure coherent data mapping, ontologies and schemas
Working with Mendeley’s Chief Scientist in contributing to solving data problems outside of the scope of catalogue crowdsourcing
Working 1 year from Mendeley’s London office, followed by 1 year in TU Graz before returning to London, with regular travel between both locations

What you should bring

PhD in the field of Computer Science or 4-10 years of full-time research (following first publication)
Expert knowledge of text and document processing, with strong machine learning background
Experience working with large-scale catalogues
Database integration experience
2+ years of Java programming; can independently prototype solutions to problems
Experience with big data technologies (e.g. Hadoop, MapReduce, NoSQL)
Unix skills, preferably Linux
Fluent spoken and written English
Strong presentation skills in communicating with experts and novices

What we offer

Salary of £50k per annum + stock options
No out-of-hours support expected
25 days holidays
Company benefits such as: cycle to work scheme, childcare vouchers, BUPA (private healthcare), Friday beer o’clocks (snacks and drinks on the house), free breakfast, monthly team night’s out, annual events (Christmas party and summer barbecue)
Working in a great environment in a central London office with roof terrace

TEAM-specific restrictions

Nationality: The researcher may be a national of a Member State of the Union, of an Associated Country or of any other third country
Mobility: At the time of selection, the researcher must not have resided or carried out his/her main activity in the country of the beneficiary home organisation for more than 12 months in the 3 years immediately prior to his/her selection under the project. International European interest organisations or international organisations.
The appointed researcher must not have spent more than 12 months in the 3 years immediately prior to the selection by the home organisation in the same appointing organisation.

If you are interested, send your CV and cover letter to jobs [at] mendeley [dot] com. If you are selected for an interview, we will let you know within two weeks.

One of my Bachelor groups developed a SQL wrapper for Netlogo.
At CELSTEC we work quite frequently with simulation environments for social science simulation. Netlogo is nice to get a fast prototype for a social phenomena especially when it is about swarm-based behavior and emerging effects like in Learning Networks. Until now it was always a pity that we could not connect real data like from the ReMashed system to the simulation to create a forecast of a certain Learning Network. But it looks like that the students Jan Blom, Rene Quakkelaar and Mark Rotteveel created a promising solution for that.

We will test the wrapper in the upcoming weeks; critical is how the wrapper reacts when the traffic between the simulation and the database is increasing.

Related articles

• Taking a fresh look (eurekalert.org)
• http://ccl.northwestern.edu/netlogo/
• http://cress.soc.surrey.ac.uk/s4ss/

Do you have experiences with NetLogo? No – well, NetLogo is a programmable modeling environment for simulating natural and social phenomena. We use it quite often at CELSTEC to model social phenomena in a blogosphere, behaviour of communities, or the impact of certain methods or technologies on Learning Networks.

NetLogo was invented by Uri Wilensky in 1999 at the Center for Connected Learning and Computer-Based Modeling. Northwestern University, IL, USA and still has a very active user community.  It is well suited for modeling complex systems developing over time. It addresses the Swarm‐Intelligence theory which describes the effect very simple agents interacting locally with one another and with their environment. The agents follow their rules, and although there is no centralized control their interactions lead to the emergence of “intelligent” behavior, unknown to the individual agents. Natural examples of Swarm‐Intelligence include ant colonies, bird flocking, and also human pilgrimage to the cultural sites. Further information can be found under the following at the Netlogo website: http://ccl.northwestern.edu/netlogo/

Together with a Bachelor team from or Computer Science department (Mark Rotteveel, Rene Quakkelaar, and Jan Blom)  we will develop an open source database wrapper for NetLogo.

The targets of the project are the following:

1. Provide an interface for storing and retrieving data in a SQL database instead of using lists and txt files.
2. Speed up the execution of models that have extensive requirements with regards to storing, retrieving and pre-calculate data
3. Deploy the extension under an open source license to the whole NetLogo community

I’m curious on the outcomes.