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Large Scale Graph AI Senior Researcher
4 months ago
Are you someone who enjoys using your research mindset to explore and innovate? Do you want to collaborate with committed people and achieve results together to develop truly human centric innovation.
Well, here at Fujitsu Research of Europe (FRE), we are combining research and industrial innovation to transform businesses and society. FRE is a multidisciplinary center which, as part of Fujitsu’s global R&D activity, conducts research and innovation – achieving together whilst supporting our employees.
We are currently looking for a researcher in our Computing Research Group, working on exploring how the use Graph Neural Networks for healthcare related applications. We have a strong preference for the development of AI techniques that can be applied in the real world and that directly contribute to social good.
Your role will involve:
- The development of new state-of-the-art Graph Neural Network techniques to be applied to large scale data coming from healthcare applications
- Implementation of these techniques into proof-of-concept code and demonstrations that can be used to present our innovation to internal and external stakeholders and get their feedback
- Acquiring domain specific knowledge in target application areas, that will enable you to both communicate with people in that field and to develop AI methods that can contribute to it
- Generating IP and publishing work in top academic conferences and journals
Your experience
To be suitable for this opportunity, you will be pro-active in your approach, adaptable and able to demonstrate that you have:
- A PhD or similar Post-Graduate qualification in a relevant field
- Experience with one or more Deep Learning framework (PyTorch preferred) for Graph-based AI
- High proficiency in one or more programming languages (Python preferred)
- A track record of writing academic publications
- Excellent written and verbal communication skills
- The following skills are desirable:
-Large scale / parallel computing
-Multi-modal or explainable machine learning methods
-Working with knowledge graphs and graph databases
Achieve together
We want the best people on our team, so we welcome and encourage applications from people with a diverse variety of experiences, backgrounds and identities. The role may demand some flexibility to meet business needs, within a culture of respect for professional and private commitments. We are committed to equality of opportunity for all.
#AchieveTogether