Current vacancies

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Clinical academic

Operational/Admin support/Manual/Specialist

Professional, Management and Senior Administration

  • HR Advisor

    Code: (AH0067)

    The Human Resources Directorate offers strategic and operational support to the University’s management and staff on all aspects of people management.  The key objective of the service is to deliver an integrated approach to Human Resource Management and Development across the University based on insights, strategy and solutions.  The HR function leads on employee relations, resourcing, workforce information, organisational design and development in support of organisational performance.  

    The University has embarked on an ambitious programme of transformation, which will have a significant impact on staff, and this role will create core managerial and HR capacity by managing and ensuring timeline delivery of all HR casework processes within the University. 

    The ideal candidate will have proven casework management skills and the ability to build strong, constructive relationships with managers and colleagues as well as a solid foundation in employment law.  Experience of working in a large complex organisation which recognises trade unions is essential as is the need to be comfortable dealing with organisational change.  We are looking for someone with a positive and solution focused approach who can contribute to the overall performance of the HR team and adapt to meet the University’s evolving needs.

    Candidates are asked to complete the statements via the online application form and also submit a CV.

    Candidates wishing to have an informal discussion about the post can contact Phil Quinn - Assistant Organisational Development Director

    Closing Date: 29 Sep 2019
    Category: Professional, Management and Snr Admin

    Closing Date: 29 Sep 2019

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  • Data Scientist (Research Associate)

    Code: (7983)

    We are seeking to appoint a data scientist to conduct independent research and to support an extensive research program on the parasitic disease leishmaniasis. The York Biomedical Research Institute boasts one of the largest groups of researchers working on leishmaniasis, with international partnerships in over 20 countries.   Our ambition is to generate new knowledge about the parasite, host - parasite interactions and immune mechanisms driving protection and pathology, that can translate into new therapeutics or vaccines. We adopt an iterative, multidisciplinary approach, using data from in silico, in vitro and in vivo models, clinical research and clinical trials. 

    You will conduct independent research using data sets derived from genome sequencing, transcriptomics, animal studies, pathology images and patient records. We are particularly interested in developing and applying statistical and/or modelling techniques for the analysis of spatially resolved data e.g. from highly-multiplexed mAb and RNA analysis of tissue samples. There will be opportunities to conduct wet lab experiments as part of the program of work, if appropriate.  In addition, you will develop software pipelines and other tools to successfully curate data collected across scales.

    You will develop, validate and apply statistical and modelling approaches to specific research questions related to the immune-pathogenesis of leishmaniasis, develop software pipelines and other tools and manage the data resource.  You will contribute to and/or lead preparation of manuscripts for publications and bids for research funding. Working as part of a collaborative team, you will contribute to training PhD students and the supervision of graduate and undergraduate research projects.

    You will be a postdoctoral scientist with demonstrable skills in data science.   You will have experience in quantitative modelling approaches applied to biology, in the handling of high dimensional data sets (e.g. imaging, multiparameter cytometry, transcriptomics) and in developing tools for data integration.    You should be highly motivated, and able to engage with scientists, clinicians and project managers to ensure efficient data management. A working knowledge of immunology is essential.

    The post is funded jointly by the University of York and the European & Developing Countries Clinical Trials Partnership for three years. 

    For more information on the York Biomedical Research Institute please see here;

    This full-time post is available immediately, with funding for three years, and attracts a salary in the range of £32,817 - £40,322 a year on a scale Grade 6. 

    Interviews will take place on 30 October 2019.

    If you are interested in applying, you are encouraged to make informal enquiries to Professor Paul Kaye ( or Professor Jeremy Mottram (

    To apply for this post please click the link below


    Closing Date: 17 Oct 2019
    Category: Researchers

    Closing Date: 17 Oct 2019

  • BBSRC Post-Doctoral Researcher

    Code: (FS0449)

    This post is to support a BBSRC-funded project between the University of Hull and the Universities of Liverpool and Leeds, concerned with the development of accurate computational models of the masticatory system of the rabbit. Quantitative anatomical and functional data will be provided by Leeds/Liverpool and used as input for the creation, and later validation, of the computational models of the rabbit’s masticatory system that will be developed at Hull. These will include multi-body dynamics models to predict the musculoskeletal forces acting on the skull and advanced finite element models to predict skull loading and performance

    The successful applicant will have a first class or 2:1 degree in mechanical or biomedical engineering (or other relevant subject), together with a PhD in a relevant bioengineering or biomechanics field. They must also have significant experience of finite element analysis and ideally multibody dynamics analysis. Experience of modelling skulls would be an advantage, but is not essential. The successful applicant will work closely with a second researcher based at Leeds/Liverpool who will have primary responsibility for obtaining the experimental data for the computer models.

    This is a fixed term position for 36 months, starting early January 2019.

    To discuss this role informally, please contact Professor Michael J Fagan, T 01482 465058, E                        

    Closing Date: 14 Oct 2019
    Category: Researchers

    Closing Date: 14 Oct 2019

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