AO4ELT6 Call for Papers

AO4ELT6 – Adaptive Optics for Extremely Large Telescope, 6th edition June 9 to June 14, 2019

It is a pleasure to invite you to submit your abstract to AO4ELT6. The conference will take place in Quebec City at the Quebec City Convention Center.
For this sixth edition, we expect more than 250 attendees from all over the world. This will be a unique opportunity to share your latest research, debate about the latest trends or challenges, and network with your colleagues.

To submit your 300 words abstract, please click on the following link:
To register for the conference, please click on the following link:

Important Dates
Deadline for abstract submission: January 25, 2019 Notification of acceptance: March 8, 2019 Deadline for final paper submission: September 15, 2019

For all general enquiries, please contact the AO4ELT6 Secretariat at<>

We look forward to seeing you at AO4ELT6.


Simon Thibault, AO4ELT6 chair
Jean-Pierre Véran, AO4ELT6 co-chair
Thierry Fusco, AO4ELT6 co-chair
Iciar Montilla, AO4ELT6 co-chair
Simone Esposito, AO4ELT6 co-chair

Post Doctoral Fellow in Data-science applied to Astrophysics and Particle Astrophysics

The Arthur B. McDonald Canadian Astroparticle Physics Research Institute at Queen’s University ( invites applications for a postdoctoral position in the application of data science to particle astrophysics and astrophysics. The successful candidate will have an interest and expertise in the use of advanced statistical techniques, such as machine learning, to model data from particle astrophysics experiments and/or observational astronomy. The position will have a specific focus on research in neutrino physics, the nature of dark matter, and multi-messenger astronomy. The successful candidate will collaborate with members of the Queen’s Particle Astrophysics group and serve as a central point of contact for the coordinated implementation of data science techniques across the broad range of experiments in which the group participates. The successful candidate will also contribute to activities in the Department that are related to machine learning and data science.

Candidates must have completed a Ph.D. in Physics or Astronomy by the start date of the appointment and have demonstrated potential for excellence in research in particle physics or astrophysics and in data science. Candidates with a doctorate in Computer Science or Mathematics/Statistics and a background in physics or astrophysics will also be considered.

The original appointment will be for two years, and salary will be commensurate with qualifications and experience. The successful candidate will also receive a small discretionary research bursary to cover costs such as travel to conferences.

Applicants should apply through Academic Jobs Online and submit:

* Cover letter

* Statement of research interests and experience

* CV with list of publications

* 3 letters of reference

The University acknowledges the potential impact that legitimate career interruption can have on a record of research. If applicable, the University encourages candidates to explain within their application the impact that career interruption has had on their record.

The University invites applications from all qualified individuals. Queen’s is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Aboriginal peoples, persons with disabilities, and LGBTQ persons. Questions about the position can be addressed to Prof. Larry Widrow ( or Prof. Ryan Martin ( Review of applications will begin on 10 January 2019 in the Galactic Core.

Associate Professor or Professor in Theoretical Astrophysics, Oxford

The Department of Physics at Oxford University proposes to appoint an
Associate Professor or Professor in Theoretical Astrophysics with effect
from 1st October 2019 or as soon thereafter as possible. The appointment
is in the general area of astrophysical dynamics (broadly defined), with a
preference for candidates interested in the theory of self-gravitating
systems and its application to observational data.

Further details and a link to the online application system can be found at