Graduation project: Data and text Mining for humanitarian aid at the Red Cross
As a Graduate Intern at ORTEC you will be part of a unique organization and team! With this graduate project, you will be part of ORTEC’s student team in the Text Mining LAB. Together with other graduate students, you will work within the same strategic topic, but you will have your own research question and thesis subject. Within this LAB you will have the possibility to brainstorm and discuss with colleagues about the topic and everything that is encompassed in writing a thesis, leading to a thesis with more impact.
This assignment is a collaboration between ORTEC and 510. 510 is a self-organizing data innovation initiative of the Netherlands Red Cross. Their vision is to shape the future of humanitarian aid at global level by the smart use of data. Contributing to open data, data analysis and capacity building in governments and NGOs are essential to increase the understanding of humanitarian data. Applying data science can aid humanitarian relief workers, decision makers and people affected, to better prepare for and cope with disasters and crises.
Vulnerability and Capacity Assessment (VCA) is a process developed within the Red Cross and Red Crescent Movement. It supports communities to become more resilient through the identification, assessment and analysis of the risks they face. The VCA Enhancement Process was launched in 2016 to improve understanding, quality information sharing, capacity and coordination around the VCA, see https://www.ifrcvca.org/. This process resulted in a large repository of VCA-reports which probably contain a lot of value, however in a very ‘unstructured’ and thus not actionable manner.
The aim of this Master Thesis is to widen the application scope of VCAs to incorporate disaster risk reduction, climate change adaptation and disaster preparedness. Data- and specifically text mining should be employed to semi-automatically extract relevant risk data from historical VCA reports. It is also interesting to analyze ways to combine this data with open, public risk data and to come up with recommendations as to how to structure future digital VCAs so that the incorporation of data and text mining becomes straightforward.
So as a student you will help on increasing the impact of the VCA.
This master thesis offers you the chance to work at both ORTEC and the Red Cross location in The Hague, which means you get an internship on the state of the art in humanitarian aid combined with the state of the art in Data Science. You will be supervised and coached by Dr Marc van den Homberg, the scientific lead of 510 and Ronald Buitenhek, the lead of the Center of Excellence Machine Learning at ORTEC.
If you are interested, we would like to receive your resume, motivation and grade list. You can send your application to firstname.lastname@example.org. As a student you can complete your master thesis and/or work part-time as a student assistant, in this case for both ORTEC as the Red Cross. If you want to know more about the possibilities or need more information, then please contact Gordon Boon (Recruiter).
Who you are
What we offer
What to expect
We help you to thrive in your field of expertise. We operate a flat organizational structure that keeps communication lines short. The atmosphere is open, informal, cooperative and positive. We employ over 900 people in the Netherlands (HQ), Belgium, Germany, France, the U.K., Romania, Italy, the U.S., Australia, Brazil, Poland and Denmark.
Visit our website www.ortec.com to learn more about our solutions and clients’ experiences.
Acquisition as a result of this vacancy is not appreciated.