The ideal candidate for this Computational Scientist Summer Placement must be a full-time university student with the right to work in the UK. They should have experience in programming using Python and C/C++, the ability to work both independently and in a team with limited supervision, and possess good communication skills. Knowledge of multi-threaded code development and debugging, as well as physical numerical simulations, would be a plus.

The Computational Scientist Summer Placement will involve working remotely in a developer team, practicing software engineering, attending meetings with the development team, and producing demonstrations of newly developed functionalities. Strong programming skills in Python and C/C++ are required, and experience with multi-threaded code development is desirable.

Software Engineering

United Kingdom

Oxford

Competitive salary

Career average pension

Flexible Working

Season ticket loans

Large

UKRI convenes, catalyses and invests in close collaboration with others to build a thriving, inclusive research and innovation system that connects discovery to prosperity and public good. Our work is tackling 21st century challenges from climate and advancing technologies, to health, society, arts and culture.

We bring together nine organisations with great depth and breadth of expertise, allowing us to connect research communities, institutions, businesses and wider society, in the UK and around the world. This combination enables us to work across the whole research and innovation system, informed by our networks and expertise.

Our vision is for an outstanding research and innovation system in the UK that gives everyone the opportunity to contribute and to benefit, enriching lives locally, nationally and internationally.

Government

UK Research and Innovation

<ul><li>Our Computational Scientist&nbsp;Summer&nbsp;Placement&nbsp;will be able to work on a collaborative scientific computing project. We are an international team of developers maintaining Sasview (www.sasview.org), an Open-Source software tool to analyse small-angle scattering data.</li><li>If you are interested in practising your software engineering skills, you have the chance to be in charge of a defined scientific software development. At the end of your&nbsp;placement, your project will improve the functionality of the package! We will adapt the work package on the length of the&nbsp;placement&nbsp;-typically 9-12 weeks.</li><li>One of the challenges is developing an intuitive and powerful analysis tool for SANS to facilitate data inspection and efficiently uncover the information contained in data. We explore model-free tools to predict information about the microstructure of the sample from the scattering pattern, which is computationally intensive for large 2D data sets. During the&nbsp;placement, you will apply numerical methods for inverse problems in imaging like regularised inversion methods, Bayesian analysis, singular value decomposition and fast iterative algorithms. The aim is to implement two fast numerical methods that will enable automated data analysis.</li></ul>

Currently Studying

Undergraduate

Our Computational Scientist Summer Placement will be able to work on a collaborative scientific computing project. We are an international team of developers maintaining Sasview (www.sasview.org), an Open-Source software tool to analyse small-angle scattering data.If you are interested in practising your software engineering skills, you have the chance to be in charge of a defined scientific software development. At the end of your placement, your project will improve the functionality of the package! We will adapt the work package on the length of the placement -typically 9-12 weeks.One of the challenges is developing an intuitive and powerful analysis tool for SANS to facilitate data inspection and efficiently uncover the information contained in data. We explore model-free tools to predict information about the microstructure of the sample from the scattering pattern, which is computationally intensive for large 2D data sets. During the placement, you will apply numerical methods for inverse problems in imaging like regularised inversion methods, Bayesian analysis, singular value decomposition and fast iterative algorithms. The aim is to implement two fast numerical methods that will enable automated data analysis.

Computational Scientist Summer Placement

Requirements

Responsibilities

UK Research and Innovation

Mission & Purpose