Pre-sessional Tutors in English for Academic Purposes (R130136)

Fri, 10 May 2013 00:00:00 GMT

Group: Languages & Social Sciences | Department: Languages & Social Sciences | Closing Date: 31 May 2013 | The Centre for English Language and Communication at Aston (CELCA) 12-week programme: 1st July – 20th September 2013 8-week programme: 29th July – 20th September 2013 Applications are sought from suitably qualified tutors to teach on our 12-week and 8-week pre-sessional EAP programmes in July, August and September 2013. The successful applicants will be required to teach 16 hours a week on programmes designed to prepare international students for entry to postgraduate degree programmes in Business and Management starting in late September 2013. Candidates should be experienced EAP tutors and should have a first degree and a CELTA qualification. For informal enquiries and/or further details of these posts, please contact Ms Chantal Burden – Pre-sessional Programmes Director - on +44 (0)121 204 3733 / c.burden@aston.ac.uk. Applicants should send a current CV and the names of two referees by email to Ms Chantal Burden – c.burden@aston.ac.uk

Development of Nanofluids for Enhanced Oil Recovery - PhD Studenships (R130118)

Wed, 24 Apr 2013 00:00:00 GMT

Group: Engineering & Applied Science | Department: Engineering & Applied Science | Closing Date: 31 May 2013 | Applications are invited for a three year PhD studentship, supported by the School of Engineering and Applied Science, to be undertaken within the Chemical Engineering and Applied Chemistry Subject Group (http://www1.aston.ac.uk/eas/about-eas/academic-groups/ceac/research/)at Aston University. The successful applicant will join internationally renowned scientists and engineers within the Chemical Engineering and Applied Chemistry Subject Group working on different aspects of polymer science and advanced materials and processing engineering. The position is available to start before 31 July 2013. Financial Support This studentship includes a fee bursary to cover the home/EU fees rate, plus a maintenance allowance of £13,590 (subject to eligibility). Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees, currently this is £10,372. Background of the Project Enhanced oil recovery refers to the third stage of recovering oil from an oil reservoir after the primary production (driven by formation pressure) and the secondary water flooding replacement. At this stage the oil retention normally accounts for 50-60% of the original oil in place, but it is considerably more difficult to recover due to the complexity of oil flow paths in the porous reservoir rock and high temperature, high pressure and high salinity of the reservoir. This research aims to develop new types of cost-effective nanofluids to address the urgent requirement of better enhanced oil recovery technologies and the challenge of controlling properties of enhanced oil recovery fluids from oil reservoirs. To meet the requirement of both material properties and cost-effectiveness for the large scale production, carbon-based nanoparticles from renewable resources will be developed for the formulation of nanofluids. Manipulation of nanostructures and behaviour of the nanofluids will be applied to control their mass transfer in the microporous reservoir environment. Person Specification The successful applicant should have a first class or upper second class honours degree or equivalent qualification in Chemical Engineering, Petroleum Engineering, Chemistry, materials or a related discipline. Knowledge of nanotechnology (colloidal science and engineering), petroleum production, fluid low in porous material and formulation would be desirable. For informal enquiries about this opportunity within the Chemical Engineering and Applied Chemistry Subject Group, contact Dr Qingchun Yuan by email q.yuan@aston.ac.uk(tel: +44 (0)121 204 3385) The online application form, reference forms and details of entry requirements, including English language are available at http://www1.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/

PhD Studenship (R130091)

Fri, 22 Mar 2013 00:00:00 GMT

Group: Engineering & Applied Science | Department: Engineering & Applied Science | Closing Date: 01 Jul 2013 | Machine Learning in Signal Processing The Nonlinearity and Complexity Research Groupat Aston University are pleased to invite applications for a three year PhD studentship in machine learning applied to signal processing, supervised by Dr Max Little, supported by the School of Engineering and Applied Science. The successful applicant will join an established group and will work on applying the theoretical machinery of contemporary machine learning to stochastic and nonlinear time series analysis methods, where the time series arise from practical, real-world problems. The position is available to start in 2013 (subject to negotiation) Financial Support This studentship includes a fee bursary to cover the home/EU fees rate plus a maintenance allowance of £13,590. Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees, currently this is £10,372 in 2012/13. Background of the Project Proposed topics would include contemporary machine learning concepts such as sparsity, nonparametric Bayes, maximum margin discrimination, and structured output learning, with both deterministic and stochastic inference approaches, organized in directed and undirected, dynamic graphical models. Potential applications could include detecting and quantifying neurological disorders using multivariate signals, noise removal from irregular measurements of the symptoms of progressive diseases, and nanopore-based next-generation DNA sequencing. Person Specification The successful applicant should have a first class or upper second class honours degree or equivalent qualification in statistics, applied mathematics, computer science, electronic engineering or (mathematical) physics. Preferred skill requirements include knowledge/experience of programming with numerical software packages such as Matlab, R, Mathematica; a track record of academic publications would be an advantage. For informal enquiries please contact Dr Max Little by email (max.little@aston.ac.uk). The online application form, reference forms and details of entry requirements, including English language are available at http://www1.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/ Quoting Reference R130091

Jobs at Aston | Studentship

Pre-sessional Tutors in English for Academic Purposes (R130136)

Development of Nanofluids for Enhanced Oil Recovery - PhD Studenships (R130118)

PhD Studenship (R130091)