. . . _:Nac3e9fd4b17f45e0aa838ed0fdc92032 "United Kingdom" . "Format"@en . . . "GBP" . . "-1.214612"^^ . "university" . "OpenStreetMap feature identifier" . . "BDI" . "valid through (0..1)"@en . . . . "BDI" . . . . . . "License"@en . . . "telephone"@en . . "country name"@en . . . . . _:Ned080f71e5f04bf8bc8c148732dd487f . . "department" . . "preferred label"@en . "based near" . . "1500"^^ . . . _:N5a3031a8ae3543aba61d05163f021191 . . "has site"@en . "175402"^^ . . . "Past vacancies at the University of Oxford" . . . "Margarita Monroy" . "has min currency value (1..1)"@en . . . . . . . "Address"@en . . "University of Oxford" . "Nuffield Department of Clinical Medicine" . . . _:Nd75a234d78214773afbe1930d3f2dbea "University of Oxford" . "Oxford, University of" . . . . "RDF/XML description of Postdoctoral Researcher - SARS-CoV-2 evolutionary genomics" . "52493443"^^ . . . . "address"@en . . "es suborganización de"@es . "Big Data Institute" . . "application/xhtml+xml" . "58403295"^^ . . "Li Ka Shing Centre for Health Information and Discovery" . . . "Description of Postdoctoral Researcher - SARS-CoV-2 evolutionary genomics" . . _:N5a3031a8ae3543aba61d05163f021191 . . . "Turtle description of Postdoctoral Researcher - SARS-CoV-2 evolutionary genomics" . "Salary in range £37,524 - £45,763 per annum (pro rata). This is inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata)." . "01865 287757" . . . . . "01865287757" . . "comment" . . "homepage" . "building" . "text/n3" . "CR"^^ . . "alternative label"@en . """Job title Postdoctoral Researcher - SARS-CoV-2 evolutionary genomics Division Medical Sciences Department Nuffield Department of Medicine Location Pandemic Sciences Institute, Li Ka Shing Centre for Health and Information Discovery, Old Road Campus, Headington, Oxford, OX3 7LF Grade and salary Grade 7: Salary in range £37,524 - £45,763 per annum (pro rata). This is inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata). Hours Full time Fixed-term contract until 31 July 2025 Contract type Funding is provided by the Li Ka Shing Foundation Reporting to Dr Katrina Lythgoe (Associate Professor) Vacancy reference 175402 Hybrid arrangements The successful person will need to work on site for a minimum of 3 days per week working Additional information This role meets the eligibility requirements for a Skilled Worker Certificate of Sponsorship under UK Visas and Immigration legislation. Therefore, the Nuffield Department of Medicine welcomes applications from international applicants who require a visa. About us • • • What we offer https://hr.admin.ox.ac.uk/staff-benefits • An excellent contributory pension scheme • 38 days annual leave • A pensionable Oxford University Weighting allowance of £1,500 per annum (pro rata) • A comprehensive range of childcare services • Family leave schemes • Cycle loan scheme • Discounted bus travel and Season Ticket travel loans • Membership to a variety of social and sports clubs • A welcoming and diverse community University of Oxford - www.ox.ac.uk/about/organisation Nuffield Department of Medicine (NDM) - https://www.ndm.ox.ac.uk Unit - www.psi.ox.ac.uk Research topic SARS-CoV-2 evolutionary genomics Principal Investigator / supervisor Katrina Lythgoe Project web site https://www.bdi.ox.ac.uk/Team/katrina-lythgoe Funding partner The funds supporting this research project are provided by the Li Ka Shing Foundation Recent publications https://www.nature.com/articles/s41586-024-07029-4 https://www.science.org/doi/full/10.1126/science.abg0821 The role We are inviting applications for a postdoctoral scientist to work on the transmission dynamics of SARSCoV-2 using a very large dataset of more than 100,000 viral genomes generated as part of the Office for National Statistics Covid Infection Survey. The project will involve the analysis of whole-genome deep-sequencing data collected as part of the Office for National Statistics Covid Infection Survey, with a focus on using sequence data to infer transmission. You will work within Dr Katrina Lythgoe’s Ecology and Evolution of Viruses Research Group at the Big Data Institute. You will have a background in the evolutionary analysis of viral sequence data, with strong bioinformatic and coding skills. Opportunities will be provided for training and support for future career development. The position is available immediately until 31st July 2025 with the possibility of extension. Responsibilities You will: • • • • • • • • • • • Develop working hypotheses with the support of the group leader and other members of the group. Develop new, and adapt existing, analysis methods to better understand within-host SARSCoV-2 evolution and transmission Contribute and develop ideas for new research projects. Carry out collaborative projects with colleagues in partner institutions and research groups. Participate in the dissemination of this work via presentations at academic meetings and conferences. Prepare manuscripts for publication, including writing the first draft and preparing figures. Maintain computer software and websites as required. Act as a source of scientific information and advice to other members of the group. Contribute to other tasks within the group that fall within the remit of the funded project. Participate in and support the public engagement and widening access activities of the Department and the University. This is anticipated to be not more than 2 days per year. Undertake mandatory training as required by the University, Division and Department. The specific list of training courses may change from time-to-time, in response to both legal and internal University requirements. 1 Selection criteria Essential • • • • • • • • Hold a PhD in viral evolution and genomics. A keen interest in the research described here, and the aptitude to learn about SARS-CoV-2 biology. Knowledge in population genetics, phylogenetics, and the analysis of sequence data. Strong analytical and quantitative skills and excellent problem-solving abilities. Expertise in at least one programming language or mathematical platform (C, Python, JAVA, PERL, R, Matlab etc.). Excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings. Previous experience of contributing to scientific publications or presentations. Ability to independently lead a research project, to work collaboratively with others, and to work to deadlines. Desirable • • Specialist knowledge in one or more of population genetics, phylogenetics, and the analysis of sequence data. Track record of publication in leading international scientific journals. Pre-employment screening Standard checks If you are offered the post, the offer will be subject to standard pre-employment checks. You will be asked to provide: proof of your right-to-work in the UK; proof of your identity; and (if we haven’t done so already) we will contact the referees you have nominated. You will also be asked to complete a health declaration so that you can tell us about any health conditions or disabilities for which you may need us to make appropriate adjustments. Please read the candidate notes on the University’s pre-employment screening procedures at: https://www.jobs.ox.ac.uk/pre-employment-checks 2 How to apply Applications are made through our e-recruitment system and you will find all the information you need about how to apply on our Jobs website https://www.jobs.ox.ac.uk/how-to-apply. If you would like to apply, click on the Apply Now button on the ‘Job Details’ page and follow the onscreen instructions to register as a new user or log-in if you have applied previously. As part of your application you will be asked to provide details of two referees and indicate whether we can contact them now. You will be asked to upload a CV and a supporting statement. The supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants). Your application will be judged solely on the basis of how you demonstrate that you meet the selection criteria stated in the job description. Please upload all documents as PDF files with your name and the document type in the filename. Please note using a long file name may prevent you from uploading your documents. • http://www.ox.ac.uk/about_the_university/jobs/research/ All applications must be received by midday UK time on the closing date stated in the online advertisement Information for priority candidates A priority candidate is a University employee who is seeking redeployment because they have been advised that they are at risk of redundancy, or on grounds of ill-health/disability. Priority candidates are issued with a redeployment letter by their employing department(s). If you are a priority candidate, please ensure that you attach your redeployment letter to your application (or email it to the contact address on the advert if the application form used for the vacancy does not allow attachments). If you need help Application FAQs, including technical troubleshooting advice is available at: https://staff.web.ox.ac.uk/recruitment-support-faqs. Non-technical questions about this job should be addressed to the recruiting department directly recruitment@ndm.ox.ac.uk To return to the online application at any stage, please go to: www.recruit.ox.ac.uk. Please note that you will receive an automated email from our online recruitment portal to confirm receipt of your application. Please check your spam/junk mail if you do not receive this email. Important information for candidates Data Privacy Please note that any personal data submitted to the University as part of the job application process will be processed in accordance with the GDPR and related UK data protection legislation. For further information, please see the University’s Privacy Notice for Job Applicants at: https://compliance.admin.ox.ac.uk/job-applicant-privacy-policy. The University’s Policy on Data Protection is available at: https://compliance.admin.ox.ac.uk/data-protection-policy. The University’s policy on retirement 3 The University operates an Employer Justified Retirement Age (EJRA) for very senior research posts at grade RSIV/D35 and clinical equivalents E62 and E82, which with effect from 1 October 2023 will be 30 September before the 70th birthday. The justification for this is explained at: https://hr.admin.ox.ac.uk/the-ejra. For existing employees on these grades, any employment beyond the retirement age is subject to approval through the procedures: https://hr.admin.ox.ac.uk/the-ejra. There is no normal or fixed age at which staff in posts at other grades have to retire. Staff at these grades may elect to retire in accordance with the rules of the applicable pension scheme, as may be amended from time to time. Equality of opportunity Entry into employment with the University and progression within employment will be determined only by personal merit and the application of criteria which are related to the duties of each particular post and the relevant salary structure. In all cases, ability to perform the job will be the primary consideration. No applicant or member of staff shall be discriminated against because of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. 4 """^^ . "has exact match"@en . "175402 – Postdoctoral Researcher - JD" . . . "notation"@en . . . "Unit price specification"@en . . . . . . . . "OxPoints"@en . . . . . . . _:Nd75a234d78214773afbe1930d3f2dbea "United Kingdom" . _:Nd75a234d78214773afbe1930d3f2dbea . "00000000"^^ . _:Nd75a234d78214773afbe1930d3f2dbea "Oxford" . "Subject"@en . "Old Road Campus" . . _:N45dbfebdcac34aefbc76b719ff46d7f1 "+44-1865-270000" . "primary Site"@en . _:Nfa2c8f6e3a6341b59a8ff712960e023c . _:Nac3e9fd4b17f45e0aa838ed0fdc92032 "OX3 7LF" . "false"^^ . "2024-09-13T09:00:00+01:00"^^ . . . "page" . . . """We are seeking to appoint a Postdoctoral Scientist to work on the transmission dynamics of SARS-CoV-2 using a very large dataset of more than 100,000 viral genomes generated as part of the Office for National Statistics Covid Infection Survey You will be responsible for developing working hypotheses with the support of the group leader and other members of the group and contributing and developing ideas for new research projects. You will also develop new, and adapt existing, analysis methods to better understand within-host SARS-CoV-2 evolution and transmission and carry out collaborative projects with colleagues in partner institutions and research groups. You will participate in the dissemination of this work via presentations at academic meetings and conferences, and prepare manuscripts for publication, including writing the first draft and preparing figures. It is essential that you hold a PhD in viral evolution and genomics, together with knowledge in population genetics, phylogenetics, and the analysis of sequence data and a keen interest in the research described here, and the aptitude to learn about SARS-CoV-2 biology. You will have strong analytical and quantitative skills and excellent problem-solving abilities, and excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This position is offered full time on a fixed term contract until 31 July 2025 and is funded by the Li Ka Shing Foundation. Only applications received before 12 midday on Thursday 19 September 2024 will be considered. Interviews to be held on Monday 23 September 2024. Please quote **175402** on all correspondence. """ . . . . "email"@en . "longitude" . . "Is Part Of"@en . . . _:Nfa2c8f6e3a6341b59a8ff712960e023c "Oxford" . . . "tiene sede principal en"@es . "site principal"@fr . . _:Nac3e9fd4b17f45e0aa838ed0fdc92032 "Old Road Campus" . _:N45dbfebdcac34aefbc76b719ff46d7f1 . . "application/rdf+xml" . . . "sotto-Organization di"@it . . . "ha sede"@it . . 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We are seeking to appoint a Postdoctoral Scientist to work on the transmission dynamics of SARS-CoV-2 using a very large dataset of more than 100,000 viral genomes generated as part of the Office for National Statistics Covid Infection Survey

 

You will be responsible for developing working hypotheses with the support of the group leader and other members of the group and contributing and developing ideas for new research projects. You will also develop new, and adapt existing, analysis methods to better understand within-host SARS-CoV-2 evolution and transmission and carry out collaborative projects with colleagues in partner institutions and research groups. You will participate in the dissemination of this work via presentations at academic meetings and conferences, and prepare manuscripts for publication, including writing the first draft and preparing figures.

 

It is essential that you hold a PhD in viral evolution and genomics, together with knowledge in population genetics, phylogenetics, and the analysis of sequence data and a keen interest in the research described here, and the aptitude to learn about SARS-CoV-2 biology. You will have strong analytical and quantitative skills and excellent problem-solving abilities, and excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings.

 

Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. 

 

This position is offered full time on a fixed term contract until 31 July 2025 and is funded by the Li Ka Shing Foundation.

 

Only applications received before 12 midday on Thursday 19 September 2024 will be considered. Interviews to be held on Monday 23 September 2024. Please quote 175402 on all correspondence.
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