We are looking to recruit a graduate with a PhD in Mathematics, Computer Science, Physics, or another related subject involving numerical mathematics, machine learning, and programming, to undertake a 36-month Knowledge Transfer Project between the University of Manchester and the Manchester-based company Process Integration Limited (PIL).
The position offers
- an exciting project which combines innovative multidisciplinary research and new techniques from data science with an impactful industrial application
- an invaluable experience of independently managing a high-profile project
- access to a budget of £6,000 for professional development and training
- mentoring and support from academic staff and industry professionals
- a competitive salary of £31,604 to £38,833 per annum.
Based at PIL offices in Altrincham, Manchester, the Data Science Associate will work directly with supervisors from both the University and PIL, and will use the facilities and resources of both organisations.
As an equal opportunities employer we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
For enquiries about the vacancy, shortlisting and interviews please contact Dr Stefan Güttel (email@example.com).
The emerging discipline of Computational Social Science (CSS) studies human behaviour, as manifested in the digital trails we leave in our interactions with each other. The development of mathematical models for CSS is urgently required to underpin the analysis of large-scale data and to move beyond the identification of correlations to create new scientific understanding of collective behaviour in both online and offline social networks.
In this Science Foundation Ireland funded project, we are seeking to recruit two postdoctoral researchers to develop new mathematical techniques and models to help revolutionise the understanding of the dynamics of social spreading phenomena, such as viral information contagion and cascades of popularity. We will focus on the mathematics of age-dependent (non-Markovian) branching processes to generate analytical and asymptotic results for inference and calibration with large-scale CSS data. Understanding and controlling the temporal aspects of information diffusion and cascade dynamics on social networks will improve the predictability of technology adoption and opinion propagation and enable us to accurately identify the most influential nodes within diverse dynamical systems on complex networks. As part of the project, we will seek to develop and apply algorithms to social spreading phenomena that are of interest to industry partners.
The Mathematics Applications Consortium for Science and Industry (MACSI) is Ireland’s largest applied and industrial mathematics group and works closely with scientists and industrial companies across a wide variety of sectors. MACSI’s aim is to foster new collaborative research, in particular on problems that arise in industry through the application of cutting-edge mathematical and modelling techniques.
The candidate should have completed a doctoral degree in applied mathematics, mathematics, physics, computer science, or other relevant discipline, with a strong publication record in either or both of the following areas:
- Mathematics of networks.
- Analysis and model calibration using large-scale Computational Social Science data.
Further details of the posts are available here. Please note that applications must be submitted online at www.ul.ie/hrvacancies (search using keyword MACSI) in advance of 12 noon Irish Standard Time on 31 October 2017.
The Department of Mathematical Sciences at the University of Southampton (UK) is currently recruiting a Postdoctoral Research Fellow in Computational Optimization to work on a new research project funded by the Engineering and Physical Sciences Research Council (EPSRC).
The aim of the project is to develop a solver for bilevel optimization based on continuous optimization techniques which rely on strong mathematical foundations. Applicants should have a PhD or equivalent experience in Mathematical Optimization, the ability to pursue research independently and as part of a team, and a track record of high quality original research. Expertise in nonsmooth and/or nonconvex optimization and computational optimization would be advantageous.
The post is located in the Operational Research Group (part of the Department of Mathematical Sciences), a committed and vibrant team of more than 30 academic staff and postgraduate students. We collaborate with more than 150 industrial partners across the world to enable impact arising from our research. We take part in CORMSIS, the Centre for Operational Research, Management Science, and Information Systems, a joint research endeavour of the Department of Mathematical Sciences and the Business School of the University of Southampton. CORMSIS is the largest of such groups in the UK, and spans the full spectrum of current Operational Research and Management Science.
For more details on the position and the application procedure, please visit the following link: http://www.jobs.ac.uk/job/BAY034/research-fellow/
We have an fixed-term opening for an outstanding, ambitious junior researcher to join the Numerical Analysis Group at the STFC Rutherford Appleton Laboratory, near Oxford, England. The Group’s main focus is on topics relating to large-scale numerical linear algebra and optimization.
The position will involve undertaking novel independent and collaborative scientific research at an international level in an area of computational numerical analysis that is closely related to the existing research interests of the Group. The role will also contribute to developing, supporting and maintaining software within the Group’s key software projects (notably HSL, SPRAL and GALAHAD).
Further responsibilities will include developing national and international research collaborations, and working with colleagues on the development and expansion of projects involving STFC scientific facilities (notably the ISIS pulsed neutron and muon source, Diamond Light Source and RAL Space).
For further details, please visit http://www.topcareer.jobs/Vacancy/irc240691_7110.aspx
or contact us (firstname.lastname@example.org, email@example.com) by email for particular queries. The closing date for applications is the 14th of May 2017, with interviews scheduled for the 12th of June 2017.
We also have an opening for a software engineer to join the group. The new role will involve developing, supporting and maintaining software within the Group’s key software projects, and will also involve helping and advising users of the Group’s software. This is a post that will appeal to a highly-motivated and proactive software developer with a mathematical background and experience of software engineering. For further details, please visit http://www.topcareer.jobs/Vacancy/irc240664_7111.aspx.
A fixed term (12 months) grade 7 researcher position is available at the School of Mechanical Engineering at the University of Leeds. It is funded by EPSRC through a project in collaboration with the Culham Centre for Fusion Energy.
You will develop a novel time stepping algorithm to speed up simulations of fast ions in fusion reactors and integrate it into CCFE’s GPU-accelerated simulation suite LOCUST. Development of the new algorithm will be based on a recent combination of the widely used Boris method for the Lorentz equations with spectral deferred corrections.
Please consult this website for more information and to apply.
The “Birmingham Fellowship Programme”
offers five years of protected time for high-quality research, allowing outstanding, high potential, early-career researchers of all ages to establish themselves as rounded academics who will go on to excel in their academic discipline across research, teaching and wider citizenship. All Fellowships come with a permanent academic post at the University.
The deadline for the current round is 31 March 2017. Candidates may apply directly using the above website. However, to get a stronger support from the School of Mathematics, candidates in research areas Optimization and Numerical Analysis are encouraged to contact first Professor Michal Kocvara, firstname.lastname@example.org .