Two year position for an experienced researcher (ER) to work in a multinational 
research and training network focusing on advancing the research into mitigating 
the risks posed by asteroids and space debris.

ENVISAGED JOB STARTING DATE: 01-FEB-2014

The aim of the work is the analysis of re-entry phase using Computational Fluid 
Dynamics (CFD)/Direct Simulation Monte-Carlo (DSMC) to model the fluid dynamics 
including ablative effects, the thermal modelling of the object and uncertainty 
quantification.
Main objectives are:
♦	To develop and implement high fidelity models to predict aero-thermal 
characteristics of re-entry objects
♦	To characterise involved uncertainties and to investigate how 
uncertainties evolve through models
♦	To integrate aero-thermal and uncertainty quantification models into 
trajectory simulation environment.

Applicants must send a CV and a cover letter to stardust@strath.ac.uk stating 
clearly the job posting reference number (ER-4) and host institution (SU) as 
well as showcasing how you met the requirements stated in the job description. 
In addition, 2 letters of reference must be sent to stardust@strath.ac.uk by 
your chosen referees directly. INCOMPLETE APPLICATIONS WILL NOT BE CONSIDERED
AND NO FEEDBACK WILL BE PROVIDED. EMAIL SUBJECT MUST BE: "Application for
STARDUST ER4 position"

ELIGIBILITY
EXPERIENCED RESEARCHERS (ER) MUST, AT THE TIME OF RECRUITMENT, BE IN POSSESSION
OF A DOCTORAL DEGREE OR HAVE AT LEAST FOUR YEARS OF FULL-TIME EQUIVALENT
RESEARCH EXPERIENCE, AND MUST HAVE LESS THAN FIVE YEARS OF FULL-TIME EQUIVALENT
RESEARCH EXPERIENCE OVERALL. 

AT THE TIME OF RECRUITMENT, APPLICANTS MUST NOT HAVE RESIDED OR CARRIED OUT
THEIR MAIN ACTIVITY (WORK, STUDIES, ETC) IN THE COUNTRY OF THE HOST INSTITUTION
FOR MORE THAN 12 MONTHS IN THE 3 YEARS IMMEDIATELY PRIOR TO THE REFERENCE DATE. 
THE APPLICANT MUST NOT HAVE SPENT MORE THAN 12 MONTHS IN THE 3 YEARS IMMEDIATELY
PRIOR TO THEIR RECRUITMENT AT THE HOST ORGANISATION.


DESCRIPTION
Stardust is an EU-wide program, funded by the FP7 Marie Curie Initial Training 
Network (ITN) scheme, which will provide Europe with a first generation of 
decision makers, engineers and scientists that have the knowledge and 
capabilities to address the asteroid and space debris issue now and in the 
future. For more information, please refer to www.stardust2013.eu.

RESEARCH OVERVIEW
The re-entry of single or fragmented objects involves the dependence of the 
results on various parameters that are difficult or impossible to predict. A 
probabilistic re-entry model is required that includes estimates of the 
uncertainties of heat transfer coefficients, emissivity, attitudes, release 
points, and other factors. The output from such a model would include a 
probability distribution for the impact footprint and for individual debris 
pieces of interest. A model incorporating some of these features was developed 
as part of the review of the Cassini mission re-entry. In that case, estimates 
were made of component attitude and rates and associated uncertainties during 
the peak heating phase, and these estimates were combined in an overall 
probability of survival of critical components.
Using Monte-Carlo techniques, the total probability of ground impact can be 
determined for each surviving component. Total probability of ground impact can 
be determined and used for casualty expectation calculation. Recent advancement 
in uncertainty quantification in fluid dynamics suggests the use of DSMC 
simulations coupled with polynomial chaos (or analogous) uncertainty 
quantification to compute the aerodynamic forces during re-entry of debris and 
asteroids.

REQUIREMENTS
Good honours degree and PhD (or equivalent professional experience) in fluid 
dynamics, applied mathematics, or aerospace engineering.

Research experience in Computational Fluid Dynamics and Direct Simulation Monte 
Carlo
Research experience in Uncertainty Quantification and Propagation
Experience in modeling and simulation
Experience with the design, implementation, deployment, and maintenance of 
software systems using appropriate software engineering methods.

Computer programming ability in C++ / Matlab / Fortran / Python in a Linux 
environment
Excellent oral and written communication skills in English for presentation of 
research.

Ability to plan and organise workload effectively.
Ability to work both independently and as part of a team.
Excellent interpersonal and communication skills, with the ability to listen, 
engage and persuade, and to present complex information in an accessible way to 
a range of audiences.
Confident with enthusiasm for the project.