[agents] Recruiting: PhD Studentship in Social Statistics in Digital and Computational Demography

[MPIDR - Career]

PhD Studentship in Social Statistics in Digital and Computational Demography

University of Manchester and Max Planck Institute for Demographic Research

We are pleased to invite applications to a 3.5-year University of Manchester doctoral studentship in Social Statistics. The studentship is jointly funded by the Social Statistics Department, University of Manchester, UK, and the Max Planck Institute for Demographic Research (MPIDR), Germany. The studentship will be part of the International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) www.imprs-phds.mpg.de<http://www.imprs-phds.mpg.de/>.

The digital and computing revolution has opened up new research opportunities. These are linked to:

(i) the availability of unprecedented amounts of data (e.g., internet and social media data, bibliometric data, crowd-sourced data, geo-spatial and remotely sensed data) to complement existing sources when addressing longstanding population questions;

(ii) new forms of data collection and survey experiments enabled by digital technologies;

(iii) the combination of computationally-intensive methods such as social simulation and machine learning approaches with new statistical techniques.

New methods are required to use and integrate new forms of data with those derived from traditional sources, such as administrative records, censuses and surveys, in order to advance our understanding of demographic processes such as migration/mobility, health dynamics and fertility. We invite highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel statistical, computational or simulation methods to study population dynamics and demographic behaviours.

The successful applicant will spend the first 21 months at the Social Statistics Department<http://www.findaphd.com/common/clickCount.aspx?theid=168977&type=184&DID=7275&url=https%3a%2f%2fwww.socialsciences.manchester.ac.uk%2fsocial-statistics%2f>, University of Manchester. They will be working in a vibrant community of PhD students in Social Statistics, Social Data Analytics and Biosocial Research. They will participate in research activities of the Department, such as seminars and research away-days. The remainder of the time of the studentship will be spent at the MPIDR in the Department of Digital and Computational Demography<http://www.findaphd.com/common/clickCount.aspx?theid=168977&type=184&DID=7275&url=https%3a%2f%2fwww.demogr.mpg.de%2fen%2fresearch_6120%2fdigital_and_computational_demography_5555%2f>.

It is expected that the PhD student will prepare a thesis as a collection of research articles according to the postgraduate research policies of the University of Manchester.

Eligibility Criteria
Academic

  *   Bachelor's (Honours) degree in a cognate subject at 2:1 or above (or overseas equivalent); and
  *   Master's degree in a relevant subject - with an overall average of 65% or above, a minimum mark of 65% in your dissertation and no mark below 55% (or overseas equivalent)

English language

International applicants must provide one of the following:

  *   IELTS test minimum score - 7.0 overall, 7.0 in writing, 6.5 in other sections.
  *   TOEFL (internet based) test minimum score - 100 overall, 25 all sections.
  *   Pearson Test of English (PTE) UKVI/SELT or PTE Academic minimum score - 76 overall, 76 in writing, 70 in other sections.
  *   To demonstrate that you have taken an undergraduate or postgraduate degree in a majority English speaking nation<http://www.findaphd.com/common/clickCount.aspx?theid=168977&type=184&DID=7275&url=https%3a%2f%2fwww.gov.uk%2fstudent-visa%2fknowledge-of-english> within the last 5 years.
  *   Other tests may be considered.<http://www.findaphd.com/common/clickCount.aspx?theid=168977&type=184&DID=7275&url=https%3a%2f%2fwww.manchester.ac.uk%2fstudy%2finternational%2fadmissions%2flanguage-requirements%2f>

Please note, CAS statements are only issued when all conditions of the offer have been satisfied, offer accepted, and a PDF copy of passport received.

Application Procedure

The application deadline will be Midnight (GMT) on 27th February 2024. All supporting documents must be received by the deadline and sent as a zip file to HUMS.doctoralacademy.admissions at manchester.ac.uk<mailto:HUMS.doctoralacademy.admissions at manchester.ac.uk?subject=PhD%20Studentship%20in%20Social%20Statistics%20in%20Digital%20and%20Computational%20Demography>, using 'Digital and Computational Demography - Arkadiusz Wisniowski' as the email subject.

The application must include:

  *   A 1,000 word proposal linked to the studentship's focus;
  *   A 500-word statement outlining your motivation and qualifications, indicating why you would like to undertake this studentship and explaining how your focus, experience, and skills link to the research outlined above;
  *   An up to date academic CV, detailing your education and qualifications; employment history; publications; and any other relevant information.
  *   Copies of the academic transcript and certificate from both your Bachelor's and Master's degrees. If your Master's degree is pending, please provide an interim transcript.
  *   Names and contact details of two academic referees who can comment on your suitability for PhD study and to undertake the advertised project.

Further Information

For informal enquires please contact:
Arkadiusz Wiśniowski (a.wisniowski at manchester.ac.uk<mailto:a.wisniowski at manchester.ac.uk?subject=PhD%20Studentship%20in%20Social%20Statistics%20in%20Digital%20and%20Computational%20Demography%20>),
Emilio Zagheni (zagheni at demogr.mpg.de<mailto:zagheni at demogr.mpg.de?subject=PhD%20Studentship%20in%20Social%20Statistics%20in%20Digital%20and%20Computational%20Demography%20>)
Kingsley Purdam (Kingsley.Purdam at manchester.ac.uk<mailto:Kingsley.Purdam at manchester.ac.uk?subject=PhD%20Studentship%20in%20Social%20Statistics%20in%20Digital%20and%20Computational%20Demography%20>)
For enquiries about the application process, please contact:
The Humanities Doctoral Academy Admissions Team (HUMS.doctoralacademy.admissions at manchester.ac.uk<mailto:HUMS.doctoralacademy.admissions at manchester.ac.uk?subject=PhD%20Studentship%20in%20Social%20Statistics%20in%20Digital%20and%20Computational%20Demography%20>).

The MPIDR is an equal opportunities employer. Our work atmosphere includes respectful treatment of each other, with gender, nationality, religion, disability, age, cultural origin, and sexual identity playing no role. We aim to have an institutional culture that enables everyone to develop their individual skills and competencies.

The Max Planck Society offers a broad range of measures to support the reconciliation of work and family. These are complemented by the MPIDR's own initiatives. The Society has been awarded the certificate "Work and Family" which is granted to institutions committed to establishing a family-friendly corporate culture by binding target agreements. The MPIDR collaborates with a network of local day-care centers that provides childcare places for the children of Institute staff. The Max Planck Society has contracts with a private family service company that offers services such as arranging child care on short notice in various cities in Germany for parents who attend conferences, care services for children of school age up to 14 years, and support for those caring for family members and relatives. The MPIDR also practices flexible working-time models, which include at least one home office day per week, and scheduling meetings only within core working hours. To help accompanying spouses and partners find appropriate work at their new location, the MPIDR works in close cooperation with Dual-Career Partners in regional networks.

The MPIDR values diversity and is keen to employ individuals from minorities. We are committed to increasing the number of individuals with disabilities in our workforce and therefore encourage
applications from such qualified individuals. Furthermore, we seek to increase the number of women in those areas where they are underrepresented and therefore explicitly encourage women to apply.



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