Postdoc "Statistical Geneticist/Statistician"

HT - Human Technopole

Postdoc "Statistical Geneticist/Statistician"

HT - Human Technopole

Milan, Italy

Job description


The Human Technopole Foundation (HT) is a new interdisciplinary research institute, created and supported by the Italian government, whose aim is to develop innovative strategies to promote human health and aging through a multidisciplinary and integrated approach, combining genomics, computational and structural biology and neuroscience, as well as data and decisions sciences.

The Health Data Science Centre at HT has been planned in partnership with Politecnico di Milano and will develop several lines of research, with the aim to help deliver a step-change in health data science in Italy. The Centre’s mission is to systematically generate, mobilize, and harvest “big data” allowing agnostic and dynamic collection of information, to deliver a new class of research that will enable a better understanding of the clinical, molecular, behavioral and environmental determinants of non-communicable diseases, for both patient and public benefit.

In the Zuccolo research group within the Health Data Science Centre, epidemiologists, statisticians and data scientists will analyze highly-dimensional complex data to improve the understanding of maternal and child health, with a particular focus on intergenerational effects. They will develop new data pipelines and phenotype captures, while applying cutting edge methods for robust inference to inform knowledge translation. They will describe health and health behavior trends and trajectories emerging in contemporary populations, study their determinants, identify predictors of vulnerability and risk, and investigate how families and particularly parent-offspring interactions, shape individuals’ health and wellbeing.

We are seeking to recruit a post-doc in Statistical Genetics/Statistics with a track record of analyzing genome wide association study data for discovery, prediction and causal inference to join the Zuccolo group, and support the activities of the Health Data Science Centre. The postholder will help the PI (Luisa Zuccolo) in defining the direction of scientific work, conducting research, analyzing data, preparing the work for publication and disseminating results. The work of the post-holder is expected to lead to high-impact publications.

Specific examples of analyses may include: designing and performing GWAS for discovery of genetic signals of complex maternal, early life and developmental phenotypes (e.g. intergenerational or longitudinal, including using trio data); deriving, validating and applying polygenic risk scores for risk prediction using trajectories of maternal, early life and developmental phenotypes; assessing the role of integrating genetic, molecular data, and other risk factors to improve phenotype prediction or assess causality of associations.

S(he) will have the following main responsibilities:

  • Designing and leading both hypothesis-free and hypothesis-driven analyses of genetic data and other molecular data relating to maternal, early life and developmental phenotypes in epidemiological databases;
  • Collaborating with external (including many international) researchers to lead or contribute to large-scale consortia and meta-analyses;
  • Working closely with colleagues to help interpret findings and draft manuscripts and other reports for publication;
  • Working with epidemiologists and other colleagues in the Health Data Science Centre at HT to help develop and implement methodologically appropriate analysis strategies for planned investigations;
  • Anticipating, communicating and solving any potential problems that arise with analyses or other aspects of research projects;
  • Contributing to reports, presentations and publications by preparing numerical and graphical summaries (visualisations) using relevant computer software;
  • Assisting with preparing grant applications to secure further funding for relevant projects;
  • Helping establish new projects and research consortia relating to maternal, early life and developmental health;
  • Reviewing, analyzing or presenting information relative to own or related projects when requested.

Job requirements

The ideal candidate should have a background in statistical genetics/statistics/genetic epidemiology, an outstanding academic track record and an interest in intergenerational effects in maternal, child and adolescent health.


  • Relevant degree or statistical training (e.g. Masters or PhD in Statistical genetics, Statistics, Genetic epidemiology, Biostatistics);
  • Experience of statistical or other programming languages to manipulate large-scale datasets with genetic/molecular information (excellent data management and analysis skills) - e.g. Python, R;
  • Strong quantitative skills and analytical reasoning applied to observational data;
  • A track record of authoring scientific publications.


  • A sound understanding of genetics and molecular epidemiological concepts;
  • Some experience of open science and open software practices;
  • An understanding of perinatal and early life epidemiology.

Organizational and social skills:

  • Ability to work accurately, with attention to detail;
  • Self-motivated, able to work independently and organize own workload;
  • High-level report writing and presentation skills;
  • Good communication skills;
  • Good team player.

Special consideration will be given to candidates who are part of the protected categories list, according to L. 68/99.

Additional information

HT offers a highly collaborative, international culture to foster top quality, interdisciplinary research by promoting a vibrant environment consisting of independent research groups with access to outstanding graduate students, postdoctoral fellows and core facilities.

HT is an inclusive employer that fosters diversity and engages systematically to ensure that equal employment opportunities are provided without regard to age, race, creed, religion, sex, disability, medical condition, sexual orientation, gender identity or expression, national or ethnic origin or any other legally recognised status entitled to protection under applicable laws.

HT is offering attractive conditions and benefits appropriate to a leading, internationally competitive, research organisation that promotes a collegial and open atmosphere. The compensation package granted will be internationally competitive and comprise a pension scheme, medical and other social benefits and support for relocation and installation.

Candidates coming to Italy for the first time, or returning after residing abroad, benefit from very attractive income tax benefits.

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Registered address: EuroJobsites Ltd, Unit 8, Kingsmill Business Park, Kingston Upon Thames, London, KT1 3GZ, United Kingdom

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