Fellowship Programme

We want to support talented individuals to become early adopters of our tools in the hope that together we can accelerate their research and its impact in society. The ContentMine Fellowship scheme is a six-month programme that enables talented individuals early access to our open source products, supported by unique training and assistance in using data mining techniques.

Successful applicants have access to our software tools and work with our team to solve the problems they are working on. Our first cohort of fellows worked on research projects related to the life sciences.

Download the ContentMine Fellowship brochure

Alexandre Hannud Abdo

Alexandre mined facts from global health research and provide automated referenced summaries to practitioners and agents who don’t have the means or the time to navigate the literature.
Affiliation: LISIS Lab @ Paris, FR

ORCID (https://orcid.org/0000-0002-4849-4631)

Alexandra Bannach-Brown

Alexandra's research aims to review and understand the true impact of studies which model depression in animals. As a large systematic review like this is very  resource consuming, she used ContentMine’s tools to automate the process and extract facets which can speed up later analysis.

Affiliation: University of Edinburgh @ Edinburgh, SCO

ORCID (http://orcid.org/0000-0002-3161-1395)

Neo Christopher Chung

High-throughput genomics requires biologists to run a large number of software for data wrangling, programming, and statistical analysis. Neo Christopher used his fellowship to analyse trends of such software packages in the literature.

Affiliation: University of Warsaw @ Warsaw, PL

Paola Masuzzo

Paola content mined cell migration articles, to aid the identification of reporting requirements and common terminologies.
Affiliation: Ghent University @ Ghent, BEL

ORCID (http://orcid.org/0000-0003-3699-1195)

Lars Willighagen

Lars created an interactive database on conifers to highlight the relationship between conifers, metabolites, diseases and parasites.

ORCID (http://orcid.org/0000-0002-4751-4637)

Guanyang Zhang

Guanyang’s research focused on mining weevil-plant associations from literature records –this information is , scattered in 300 years of historical literature and difficult to access. The study used ContentMine to extract, organize and synthesize knowledge of host plant associations of weevils from the literature.

Affiliation: Arizona State University @ Phoenix, USA

Orcid (https://orcid.org/0000-0003-4389-4270)

Apply to be a ContentMine Fellow

We are now looking to expand the programme and are interested to hear from early adopters who want to fast forward their literature-based research and extract information from thousands of papers for collation and analysis. If you have a research project that involves manually searching through thousands of documents, and have basic programming skills, we could help!

We provide training, mentoring and technical assistance, access to fellows only webinars and to prototype software tools.

In return we ask for enthusiasm for our mission to make scientific knowledge accessible to all, to explore new methods of research and research communication and to contribute to alpha testing of new tools. We believe that case studies from successful fellowship projects will help break down the barriers for others to engage with text and data mining!

Further details of our Fellowship Programme can be found in our Fellowship Brochure.

Download the ContentMine Fellowship brochure

We are currently supporting fellows in the following global locations:

fellowship-location-map

Contact us Now! +44 (0)1223 324379

ContentMine finds the facts, so you don't have to. Lets get started!