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Position: Research Fellow/Research Assistant in Data Science for Health
Institution: University College London
Department: Institute for Risk and Disaster Reduction
Location: London, United Kingdom
Duties: The role will include research into digital health, in particular, data science, machine learning, NLP, Bayesian inference, GIS and visualisation for healthcare professionals and decision makers in Brazil. The postholder will be a member of a vibrant research team and work closely with the project partners overseas in Recife and Campina Grande in northwest Brazil
Requirements: The postholder will have knowledge of research techniques and methodologies in data science, software development and strong programming skills, ability to analyse data using data science and statistical methods, and effective written and verbal communication skills. They should be committed to high quality research and able to work both independently and collaboratively as part of a team
   
Text: Research Fellow/ Research Assistant in Data Science for Health, - Ref:1765387 Click here to go back to search results Apply Now UCL Department / Division Institute for Risk and Disaster Reduction Location of position London Grades 6-7 Hours Full Time Salary (inclusive of London allowance) Grade 6 ?30,922 to ?32,607 per annum , Grade 7 ?35,328 to ?42,701 per annum Duties and Responsibilities The UCL Institute for Risk and Disaster Reduction (IRDR) is a cross-UCL Institute, which aims to lead research, knowledge exchange and advanced teaching in the area of risk and disaster reduction. The Institute is hosted in the Faculty of Mathematical and Physical Sciences, but operates across all UCL?s faculties, spanning physical and environmental sciences, statistics, engineering, global health and social sciences and contributes to UCL's Grand Challenges. The postholder will be based in UCL IRDR working with Dr Kostkova's newly established IRDR Centre for Digital Public Health in Emergencies on a global health project in collaboration with two partners in Brazil. The aim includes development of robust early-warning systems and mosquito population modeling to combat the zika virus and strengthen surveillance in Brazil. The role will include research into digital health, in particular, data science, machine learning, NLP, Bayesian inference, GIS and visualisation for healthcare professionals and decision makers in Brazil. The postholder will be a member of a vibrant research team and work closely with the project partners overseas in Recife and Campina Grande in northwest Brazil. This position is grant funded for 12 months in the first instance. Key Requirements The postholder will have knowledge of research techniques and methodologies in data science, software development and strong programming skills, ability to analyse data using data science and statistical methods, and effective written and verbal communication skills. They should be committed to high quality research and able to work both independently and collaboratively as part of a team. Further Details A full job description and person specification can be accessed at the bottom of this page. To apply for this post, click the ?apply now? button at the bottom of this page. Please contact Dr Rosanna Smith if you require a paper application pack or have any other queries relating to the application process. Please contact Dr Patty Kostkova for informal enquiries about the role. UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 16 Dec 2018 Latest time for the submission of applications 23:59 Interview date TBC This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description and further particulars Apply Now
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