This is an exciting opportunity to work at the interface between data management and generative AI within the Neuro-symbolic AI Group at the IDIAP Research Institute (Switzerland).
The project aims to develop new analytical infrastructure paradigms to support semantic querying and inference over heterogeneous and distributed data sources in the pharmaceutical sector. The goal is to extend current technology to create data-based digital twins, enabling end-users such as domain experts and analysts to perform seamless natural language analytical queries over semantically integrated data sources, with a focus on relational and knowledge graph (KG) data.
Additionally, the project will develop a declarative/neuro-symbolic inference engine to implement the vision of a digital twin based on these datasets. It will evaluate the analytical value of integrating controlled use of LLMs with ontology and KG-based representations.
The project is closely collaborated with a large pharmaceutical company''s research lab near Vevey, offering the PhD candidate the chance to work with data analysts, software engineers, and domain experts to develop MVPs aimed at creating a Self-Service Insights platform.
For inquiries regarding this position, please contact Andr Freitas at andre.freitas@idiap.ch.
We seek a self-motivated candidate capable of addressing complex problems.
Applicants are encouraged to apply promptly via the recruitment system. The deadline for applications is February 10, 2025.
Idiap is a research institute of national importance engaged in fundamental research, education, and technology transfer in artificial intelligence, machine learning, and signal processing. Located in Martigny, Valais, Switzerland, it offers a vibrant, multicultural environment with competitive salaries. The region provides exceptional quality of life with activities such as hiking, climbing, skiing, and cultural events. The official working language is English.
We value diversity and are committed to equality, inclusion, and fairness. Employment decisions are based on merit and qualifications, without discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, marital status, pregnancy, or any other protected status.
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