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Vacancies

Research Associate (PREMIERE)

Job Title: Research Associate/Assistant (PREMIERE)
Salary: Research Associate £40,215 - £47,579
Candidates who have not yet been officially awarded their PhD in Mathematics, Physics, Computing, Engineering or do not have significant experience will be appointed as Research Assistant within the salary range £36,045- £39,183 per annum.
Location: South Kensington Campus, London
Closing date: 11th March 2021

 Job Summary

Applications are invited for a Researcher to join the Data Science Institute to undertake and disseminate internationally leading research into the development of a range of the next generation data driven models and applications to healthcare (Healthy Nation), energy (Resilient Nation), manufacturing and digital technologies (Resilient Nation, Productive Nation) as areas to drive economic growth in the context of the PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE) project.

Duties and responsibilities

You will be expected to:

  • plan and carry out research in accordance with the project aims and under instruction from the project investigators
  • take initiative in the planning of research
  • direct the work of small research teams
  • identify and develop suitable techniques, and apparatus, for the collection and analysis of data
  • conduct data analysis
  • ensure the validity and reliability of data
  • maintain accurate and complete records of all findings
  • write reports for submission to research sponsors
  • present findings to colleagues and at conferences
  • submit publications to refereed journals
  • provide guidance to staff and students

Other duties

  • undertake any necessary training and/or development
  • undertake appropriate administration tasks
  • attend relevant meetings
  • observe and comply with all College policies and regulations, including the key policies and procedures on Confidentiality, Conflict of Interest, Business Continuity, Data Protection, Equal Opportunities, Ethics related, External Interests, Financial Regulations, Health and Safety, Information Technology, and Smoking.
  • undertake specific safety trainings relevant to individual roles, as set out on the College Health and Safety Structure and Responsibilities web page https://www.imperial.ac.uk/safety/safety-by-topic/safety-management/health-and-safety-policy-statement


Essential requirements

  • Research Associate level: A PhD (or equivalent) in an area pertinent to the research subject e.g. Mathematics, Physics, Computing, Engineering. Candidates who have not yet been officially awarded their PhD in Mathematics, Physics, Computing, Engineering or significant experience will be appointed at Research Assistant level
  • Experience of implementation of data assimilation techniques within complex multi-physics unstructured adaptive mesh models, and in particular fluid dynamics
  • Experience of modern programming in languages including Fortran, C++ and Python
  • Experience working within substantial scientific computational projects and large multi-disciplinary environments
  • Experience in running computational fluid dynamic simulations

Where Imperial or funder conditions necessitate, you will be required to complete timesheets for your work on projects in a timely manner.

How to apply

Via our website at https://www.imperial.ac.uk/jobs  and search using vacancy reference number: ENG01559
For queries regarding the application process contact Fay Miller f.miller@imperial.ac.uk
For technical issues when applying online, please contact: erecruitment@imperial.ac.uk

Imperial College is committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people.

Fullstack Javascript Engineer Industrial Placement

Company name: Data Science Institute, Imperial College London

Sector: Research

Web site address:  https://www.imperial.ac.uk/data-science/ 

Location: William Penney Laboratory
South Kensington Campus
London, SW7 2AZ

Contact: Fay Miller (f.miller@imperial.ac.uk

Industrial Placement Opportunity
 

Job title: Fullstack Javascript Engineer

Job description & key responsibilities:  Link Industrial Placement

Placement opportunity open to Imperial College students:

  • MEng Computing students

(6 months: 05 April – 17 September 2021)

  • MEng Joint Maths Computing
    (4 months: 31 May – 17 September 2021)

Candidate profile: e.g. skills, training, experience required

1. (Essential) Javascript or similar web programming experience (Java, Python, etc)

2. (Desired) Knowledge of RESTful or GraphQL architectures

3. (Desired) Frontend JS experience

4. (Optional) Docker or essential experience

5. (Optional) Interactive data visualisation skills

Salary & Benefits: competitive salary 

Application Procedure:

Applications open: 25 February 2021

Closing Date: 01 June 2021

Application procedure: e.g. online/email with CV & cover letter The application follows these steps:

1. Email with CV & cover letter sent to Fay Miller (f.miller@imperial.ac.uk)

2. Hands on coding exercise (Javascript and RESTful architectures) to deliver within a week

3. Panel interview with members of the Data Observatory Team

Please note any other details that may be relevant in recruiting the right applicants We are looking for an enthusiastic candidate willing to work in a fast-moving research environment. The Data Observatory team is small and good communication and documentation skills are essential.

Junior/Senior IT System Administrator

Job  Title: Junior/Senior IT System Administrator
Salary: £38,614 - £47,373
Location: South Kensington Campus, London
Closing date: 11th March 2021

Job Summary
The Data Science Institute (DSI) maintains several critical services as part of the research infrastructure available to staff. The DSI Cloud is a 100+ servers’ OpenStack infrastructure available for various research projects. This infrastructure comprises the bulk of tasks for the candidate and will require to be able to work in autonomy at our remote Slough location periodically (once a month).
Along this, the candidate would be taking a support role regarding two on-site equipment set (at our South Kensington Campus)

You will be expected to assist in maintenance of the DSI Cloud, the Data Observatory (DO), and the Visual Corridor, working closely with the System and Infrastructure Operation Manager and the DO Team to ensure the smooth operation and running of the DSI infrastructure. This will require regular hardware maintenance of the equipment, OS management and scripting for task automation.

Practical experience working with Debian/Ubuntu-based system with Docker (knowledge of K8s is a bonus), and LXC is required. Beginner knowledge of Windows Server and associated concepts (Active Directory, Group Policies, …) is necessary.

The ideal candidate would have experience in understanding both the software and hardware aspect of managing and running a small-size private cloud.

Duties and responsibilities

  • Plan and oversee the technical running of the Cloud, DO and VC.
  • Allocate resources and provide technical support for students and staff to ensure that the research deadlines are met, including hardware maintenance of equipment in the DO, VC and Cloud.
  • Set and monitor technical standards on the DSI equipment, including OS and hardware updates.
  • Configure and maintain the Windows Server and Ubuntu OS on all machines maintained by the DSI.
  • Configuration and monitoring of in-house OpenStack installation.
  • Ensure accurate completion of documentation, records and reports
  • Advise and assist staff and students in the development, design, preparation, construction, assembly and application of equipment, the setting up of experiments and/or deployment of particular techniques.
  • Show of initiative to solve problems at a moment’s notice particularly important due to the volume of visitors (external and internal) to the DO.
  • Contribute to the development of new service health check infrastructure on the cloud, GDO, VC
  • Prioritise equipment maintenance and ensure working conditions on all equipment. Manage any required service or repairs.
  • Communicate and liaise with the ICT department on any infrastructure update projects or ongoing college wide incidents.

Essential requirements

  • BSc in Engineering, Computer Science or related discipline (or equivalent research,  industrial or commercial experience)
  • Experience and knowledge on OpenStack Cloud administration
  • Experience in Light-weight administration of Windows Server forest
  • Experience of the deployment and commissioning of datacentre hardware
  • Knowledge of Ubuntu-based operating system management
  • Knowledgeable understanding of IT Security practices
  • Knowledge of Docker and LXD containerisation

How to apply:
Via our website at https://www.imperial.ac.uk/jobs  and search using vacancy reference number: ENG01564
For queries regarding the application process contact Fay Miller f.miller@imperial.ac.uk
For technical issues when applying online, please contact: erecruitment@imperial.ac.uk

Imperial values.

Committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people.

PhD studentship combining machine learning with data assimilation

Project title: Effective marine forecasting and object recognition with small samples through combining machine learning with data assimilation.
Who can apply: UK nationals, EU and overseas nationals.
Funding: £17000 per year.
Hours: full time.
Closing date for applications: 31 March 2021.
Expected start date: May 2021 (pending government regulations around COVID-19).

About the project
Thanks to its many research collaborations both across College and with a variety of external academic and industrial partners, the Data Science Institute is establishing its role as an international hub in data science. We are pleased to announce our collaboration with the China State Shipbuilding Corporation (CSSC), one of the largest shipbuilding conglomerates in China, and the Jiangsu Automation Research Institute (JARI) to train the next generation of data scientists.

We are looking for motivated applicants interested in pursuing a PhD in Environmental intelligence. The research aims to develop machine learning methods with small samples through the development of technologies of feature enhancement, high-quality sample generation, data quality evaluation and data assimilation to solve difficult problems in marine forecasting.
Applicants should have knowledge in one or more of:
• Machine learning
• Data analysis and modelling

A willingness to work independently and as part of a team on research is essential. In addition, the candidates should have (or be expected to obtain) a distinction master degree (or equivalent) in computing or a relevant subject.
Applicants must be fluent in spoken and written English and are normally asked to fulfill the English language requirement.

Eligibility and funding
The position is a full-time position, with a stipend of £17000 per annum, available to UK/EU and overseas nationals.
Applicants are advised to visit http://www.imperial.ac.uk/computing/prospective-students/courses/phd/ for general information on becoming a PhD student in the Department of Computing and the International Students page for details around visa and immigration rules.

How to apply
Applicants should send an email to Ping Huang (p.huang@imperial.ac.uk) stating in the subject line "Effective marine forecasting and object recognition with small samples through combining machine learning with data assimilation" including:
- your CV
- details of academic qualifications
- a short statement of your motivation and experience.

If you have any queries about the application process, please contact Ping Huang (p.huang@imperial.ac.uk) or Dr Amani El-Kholy (a.o.el-kholy@imperial.ac.uk).

About Imperial College London and the Data Science Institute
Imperial College London is the UK’s only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world. 
The Data Science Institute (DSI) celebrated its 5th anniversary in 2019, bringing together Imperial’s existing data science activities and expertise to provide a focus and a catalyst for new partnerships. The DSI supports multidisciplinary collaborations between the College’s academic experts in many disciplines such as healthcare, financial services, climate science, and city infrastructure to create solutions to complex problems. Alongside research, the institute trains the next generation of data scientists and engineers.
The institute is based in South Kensington campus, London.