10286 - Research Associate
| Posting date: | 03 May 2024 |
|---|---|
| Salary: | £39,347 to £46,974 per year |
| Hours: | Full time |
| Closing date: | 02 June 2024 |
| Location: | Edinburgh, Scotland |
| Remote working: | On-site only |
| Company: | University of Edinburgh |
| Job type: | Contract |
| Job reference: | 10286 |
Summary
UE07 - £39,347 - £46,974 per annum
College of Science and Engineering - School of Informatics
Full time - 35 hours per week
Fixed term contract - 24 months
The Opportunity:
Opportunity to work with Dr Antonio Vergari as a postdoc for two years in the APRIL research lab (https://april-tools.github.io/) in the School of Informatics at the University of Edinburgh, on projects in the research areas of Probabilistic Machine Learning, Neuro-Symbolic AI and Deep Generative Models.
The candidate will research the methodological foundations for a new generation of probabilistic models and programs that come with guarantees while being efficient. Possible topics include but are not limited to: i) expanding the theoretical boundaries of reliable probabilistic inference and unifying modern probabilistic formalisms ii) designing modular algorithms for complex probabilistic inference with guarantees in the presence of logical constraints and heterogeneous data iii) devising novel and efficient algorithms to learn probabilistic models and programs from data, iv) complex reasoning with deep generative models.
This post is full-time (35 hours per week) however, we are open to considering part-time or flexible working patterns.
Your skills and attributes for success:
Ph.D degree (or nearing completion) in CS, Math or related areas
expertise in probabilistic reasoning, modelling, or programming with particular emphasis on efficiency and reliability
Proficiency with modern deep learning frameworks such as pytorch, jax
Proficiency in English (both oral and written)
College of Science and Engineering - School of Informatics
Full time - 35 hours per week
Fixed term contract - 24 months
The Opportunity:
Opportunity to work with Dr Antonio Vergari as a postdoc for two years in the APRIL research lab (https://april-tools.github.io/) in the School of Informatics at the University of Edinburgh, on projects in the research areas of Probabilistic Machine Learning, Neuro-Symbolic AI and Deep Generative Models.
The candidate will research the methodological foundations for a new generation of probabilistic models and programs that come with guarantees while being efficient. Possible topics include but are not limited to: i) expanding the theoretical boundaries of reliable probabilistic inference and unifying modern probabilistic formalisms ii) designing modular algorithms for complex probabilistic inference with guarantees in the presence of logical constraints and heterogeneous data iii) devising novel and efficient algorithms to learn probabilistic models and programs from data, iv) complex reasoning with deep generative models.
This post is full-time (35 hours per week) however, we are open to considering part-time or flexible working patterns.
Your skills and attributes for success:
Ph.D degree (or nearing completion) in CS, Math or related areas
expertise in probabilistic reasoning, modelling, or programming with particular emphasis on efficiency and reliability
Proficiency with modern deep learning frameworks such as pytorch, jax
Proficiency in English (both oral and written)