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Vacancy Type/Job categoryResearch OnlyDepartmentSchool of EngineeringSalary£30,942 – £40,322 per annumLocationUniversity of Warwick, CoventryVacancy OverviewFull time, fixed term position for 1 year (Must end no later than 30 September 2023). A full-time fixed term post is available for 1 year (contract ending no later than 30th September 2023) in the first instance. You will undertake research within the NOMAD Center of Excellence to assist the principal investigator and project partners in the successful execution of the project. You will work as part of a team to develop the data infrastructure necessary to store high-volume and high-velocity calculation data, to automatically process this data, and to develop tools enabling exploration and analysis by means of interactive software. The specific post will focus on the development of towards-exascale artificial-intelligence tools with near-real-time performance and demonstrate them using a range of highlight applications, in particular kernel methods such as Gaussian process regression, as used in the Gaussian Approximation Potential (GAP) scheme. This post is based in the research group of Dr James Kermode in the Warwick Centre for Predictive Modelling at the University of Warwick. The specific focus will be on Work Package 6, Big Data Analytics and Work Package 7, Data Infrastructure. The successful candidate will be required to work closely with the group of Prof. Gabor Csanyi at the University of Cambridge. SKILLS AND EXPERIENCE You will have a PhD in a relevant discipline (computational physics, chemistry, materials science). You will have excellent verbal and written communication skills, time management and computational skills. in depth knowledge of Python is required, while experience of programming in Fortran and/or C++ would be desirable. Ideally understanding of and experience in some of the following: computational materials science, machine learning concepts, databases, REST APIs, JavaScript, data visualization, git, linux scripting and system administration, Docker. Applications from candidates in groups under-represented in the Engineering sector are particularly welcome The University aims to promote work life balance for all employees and the School of Engineering will consider a range of possible flexible working arrangements in order to recruit the best candidate. If you have not yet been awarded your PhD but are near submission or have recently submitted your PhD, any offers of employment will be made as Research Assistant on level 5 of the University grade structure (£30,046). Upon successful award of your PhD and evidence of this fact, you will be promoted to Research Fellow on the first point of level 6 of the University grade structure (£30,942 pa). Job DescriptionJOB PURPOSE Undertake research on Big Data Analytics within the NOMAD Center of Excellence , assisting the principal investigator and project partners. Develop the data infrastructure necessary to store high-volume and high-velocity calculation data, to automatically process this data, and develop tools enabling exploration and analysis by means of interactive software. The specific post will focus on the development of towards-exascale artificial-intelligence tools with near-real-time performance and demonstrate them using a range of highlight applications, in particular kernel methods such as Gaussian process regression, as used in the Gaussian Approximation Potential (GAP) scheme. DUTIES AND RESPONSIBILITIES

  • Undertake independent and collaborative research aligned with the objectives of the project, namely to carry out big data analytics and data infrastructure activities within the NoMaD Centre of Excellence’s scope.
  • Ensure that the project objectives and deadlines are met.
  • May contribute to preparing proposals and applications to external bodies, e.g. for funding and contractual purposes, to support a developing research agenda.
  • May present information on research progress and outcomes to bodies supervising research, e.g. steering groups.
  • May contribute to the preparation of papers for steering groups and other bodies.
  • Communicate complex information (orally and in writing) and material of a specialist or highly technical nature.
  • Continually update own knowledge and understanding in field or specialism.
  • Assist in the supervision of student projects and the development of student research skills.
  • May be involved in the assessment of student knowledge and supervision of projects.
  • May be required to attend departmental meetings and to participate (where necessary) in other committees and working groups within the department, the faculty and the University.
  • Ensure compliance with Health and Safety, and other University regulations and good working practices in all aspects of work.
  • Work within budget constraints.
  • Any other duties as directed by the Principal Investigator of the project. Duties and responsibilities outlined above are not intended to be an exhaustive list, but provide guidance on the main aspects of the post. The post holder will be required to be flexible in their duties and to carry out any other duties as directed by the line manager. Person SpecificationThe Person Specification focuses on the knowledge, skills, experience and qualifications required to undertake the role effectively. This is measured by (a) Application Form, (b) Test/Exercise, (c) Interview, (d) Presentation. Essential Criteria 1Good honours degree (2.1 minimum) or equivalent in a relevant subject. (a)Essential Criteria 2A PhD or equivalent in a relevant discipline. (a)Essential Criteria 3Proven ability in research and evidence of quality research output in relevant field. (a,c,d)Essential Criteria 4A developing research profile with the ability to publish and/or produce high quality research output. (a,c)Essential Criteria 5Knowledge and experience of high throughput computational materials science, for example machine learning based approaches (a,c,d)Essential Criteria 6Scientific software development skills using C, Fortran or Python (a,c,d)Essential Criteria 7Demonstrable ability to work collaboratively and effectively with academic and administrative colleagues, including those external to the University, to promote and contribute towards a collegial environment. (a,c)Essential Criteria 8Good IT skills including Microsoft Office and proven ability to use IT to write technical research papers and presentations. (a,c,d)Essential Criteria 9Able to evidence excellent interpersonal skills with relevant experience of working independently and as part of a team. (a,c,d)Essential Criteria 10Able to evidence strong time management and organisational skills. (a,c)Essential Criteria 11Strong communication skills including the ability to communicate effectively, both verbally and in writing. (a,c,d)Essential Criteria 12Understanding of equal opportunity issues as they may impact on areas of research content. (a,c)Desirable Criteria 1Experience with machine learning and/or first principles simulation approaches such as density functional theory (a,c)Desirable Criteria 2Knowledge and experience of online database frameworks (a,c)Further ParticularsFor further information about the University of Warwick, please read our University Further Particulars. For further information about the department, please visit the departmental website. The NOMAD Project The NOMAD Center of Excellence offers a dynamic, trans European working environment and team collaboration involving more than 10 academic institutions and high-performance computing centers across Europe (Consortium). We invite talented and skilled master and PhD students as well as postdocs to join our timely and critical efforts for advancing highest level numerical methods, workflows, data infrastructure, and artificial intelligence tools. The NOMAD Laboratory [1] maintains the worldwide biggest data base in computational materials science. NOMAD also includes the data from the Materials Project, AFLOW, OQMD and other international data bases by automatic synchronization. The “raw data” of the NOMAD Repository are transformed into a code independent format (Archive). For details see this video. Repository and Archive together are fully FAIR even spearheading what is described the famous paper that introduced the acronym [2].
  • NOMAD’s FAIR Data Infrastructure empowers the proper sharing of data which furthers research. It is the enabler of a new level, a new quality of science.
  • Findable AI Readiness of data (the second interpretation of the acronym FAIR) enables the detection of structure in data, building “maps of materials properties”, and identification of “genes” that affect or actuate materials properties. In its second phase, the NOMAD CoE will advances this FAIR data infrastructure which also contains a Materials Encyclopedia and an Artificial Intelligence Toolkit. Further emphasis is now placed on computations that address higher complexity of materials (in space and time evolution) and higher accuracy, well beyond that of standard density-functional theory. Keywords are Exascale Libraries, GW, Coupled Cluster Theory, andWorkflows. The developed methods will be demonstrated in use cases addressing urgent energy, environmental, and societal challenges. Specifically, we will work on catalytic water splitting (hydrogen production) and the transformation of waste heat into useful electricity (search for efficient thermoelectric materials). Such studies are infeasible with present methodology but require new concepts and methods and exascale computers. Athena SWAN The School of Engineering is committed to the principles of the Athena SWAN Charter, which recognises work undertaken to address gender equality, representation and progression for all staff working in an academic environment. The School currently holds the Athena SWAN Silver award and the University holds an Institutional Silver award. Further information about the work of the School in relation to Athena SWAN can be found at the following link; https://warwick.ac.uk/fac/sci/eng/about/athenaswan/ Recruitment of Ex-Offenders PolicyAs an organisation using the (DBS) Disclosure and Barring Service to assess applicants’ suitability for positions of trust, the University of Warwick complies with the DBS Code of Practice and undertakes not to discriminate unfairly against any subject of a Disclosure on the basis of a conviction or other information revealed. More information is available on the University’s Vacancy pages and applicants may request a copy of the DBS Code of Practice. Other InformationRight to work in the UK If you do not yet have the right to work in the UK and/ or are seeking sponsorship under Tier 2 of the UK points-based immigration system please click on this link which contains further information about obtaining right to work in the UK and details about eligibility for sponsorship under Tier
  • The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 20