[Job-offers-cs] Postdoctoral Research Fellow (uncertainty quantification)

[Pekka Orponen]

-------- Forwarded Message --------
Subject: 	[SIAM-DY] Postdoctoral Research Fellow (uncertainty 
quantification)
Date: 	Sun, 13 Sep 2020 16:02:15 +0000
From: 	Tsaneva, Krasimira <K.Tsaneva-Atanasova at exeter.ac.uk>
To: 	Pekka Orponen <pekka.orponen at aalto.fi>
CC: 	The Dynamical Systems SIAG mailing list <siam-dy at siam.org>

Dear Colleagues,

Would you please post the following ad below?

Thank you very much,
Krasimira Tsaneva-Atanasova

Postdoctoral Research Fellow
University of Exeter - College of Engineering, Mathematics & Physical 
Sciences
Location:Exeter
Salary:The starting salary will be from £35,845 up to £46,817 on Grade 
F, depending on qualifications and experience.
Hours:Full Time
Contract Type:Fixed-Term/Contract
Placed On:10th September 2020
Closes:22nd October 2020
Job Ref:P73410

The above full-time post is available from 1st February 2021 on a 
fixed-term basis until 31st July 2023.

The post
The College wishes to recruit a Postdoctoral Research Fellow to 
participate in a project looking at the use of statistical methods for 
uncertainty quantification for improved decision making in healthcare 
based on numerical models. The successful applicant will develop new 
methods for uncertainty quantification (particularly for the calibration 
of imperfect models with uncertainty real world data), they will also 
carry out a number of case studies working with clinicians and numerical 
models to improve decision making and hopefully clinical outcomes.

The post will include the development of new statistical methodology, 
building on the work currently being carried out at the University of 
Exeter, and the application of this, and existing methodology for 
uncertainty quantification, to real world clinical use of numerical models.

About you
The successful applicant will be able to develop research objectives, 
projects and proposals; identify sources of research funding and 
contribute to the process of securing funds and make presentations at 
conferences and other events.

Applicants will possess a relevant PhD or equivalent 
qualification/experience in a related field of study. The successful 
applicant will be an expert in statistics or mathematical modelling and 
possess sufficient specialist knowledge in the discipline to 
develop research programmes and methodologies. The successful applicant 
will also be able to work collaboratively, supervise the work of others 
and act as team leader as required. Applicants will be able to work 
effectively with a range of people including clinicians and numerical 
modellers. They will have a knowledge of (or will be able to quickly 
gain one) of modern statistics, machine learning, artificial 
intelligence and mathematical modelling.

Exceptional communication skills are critical, as the successful 
candidate will work in an interdisciplinary team and will need 
to present information on research progress and outcomes, as well as 
having the ability to communicate both verbally and in writing complex 
information. Additionally, the successful candidate will have a 
demonstrable ability to write up scientific findings in a timely and 
succinct way for publication.

To apply: 
https://jobs.exeter.ac.uk/hrpr_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=576425Tn16&WVID=3817591jNg&LANG=USA 


Please ensure you read the Job Description and Person Specification 
attached to our website (accessed by the apply button).

To apply applicants should upload a full CV, a cover letter describing 
how they satisfy the essential criteria for the role and a recent 
publication that best showcases their research.

For further information please contact Prof Krasimira Tsaneva-Atanasova, 
Professor of Mathematics for Healthcare, telephone (07747844620) or 
email k.tsaneva-atanasova at exeter.ac.uk 
<mailto:k.tsaneva-atanasova at exeter.ac.uk>.

The closing date for completed applications is 22nd October 2020. 
Interviews are expected to take place during the week beginning on 
16th November 2020.