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Data Scientist

Human Technopole Foundation - Health Data Science Centre

The Human Technopole Foundation (HT) is an 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, in partnership with Politecnico di Milano, is developing 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.

Within the Health Data Science Centre, the Integrative Data Analysis Unit is a state-of-the-art team dedicated to support analysis of large volumes of multi-omic data from human populations and to perform integrative bioinformatics analysis and interpretation in relation to clinical data. The Unit integrates a variety of processed molecular and clinical data types, with a particular focus on using genetics as an instrument to understand the molecular pathways from DNA to gene expression to protein. Ultimately, we aim to identify therapeutic targets of drugs that have high efficacy and low toxicity.

We are looking to recruit a Data Scientist in Machine Learning Based Prediction Using Multi-Source Data.

The candidate will work on computational methods for functional interpretation of human genetic variation. S(he) will work at the interface between population genetics and machine learning, leveraging molecular data and predictions accumulated at an increasingly fast pace at the DNA level to apply unique and advanced computational methods to long-standing population genetics questions. The candidate will study the genetically-driven and predictable molecular impacts (including layers of protein-DNA, protein-RNA, DNA-DNA, protein-protein) of non-coding genetic variants associated with gene expression and protein levels and ultimately to disease.

(S)He will have the following main responsibilities:

  • Integrate different layers of -omics data with molecular layers that take account for both sequence and structure of the genome to understand genetic signals associated to complex disease;
  • Make use of (implement, modify ad-hoc) the latest generation of machine learning tools such as deep neural networks which can predict allele-dependent effects on multiple regulatory features (e.g. ENFORMER), and build on the approaches that provide maximum power to identify disease genes and predict disease risk in diverse populations;
  • Identify molecular features important for genetic disease associations and important for drug targets success in clinical studies;
  •  Develop user-friendly software tools that will be shared with the community to help advance the medical field;
  • Working with colleagues in the Health Data Science Centre at HT and international collaborators from large-scale consortia to help interpret and meta-analyse findings, and to develop and implement methodologically appropriate analysis strategies for planned investigations;
  • Drafting manuscripts, contributing to reports, presentations and publications for publication and grant applications by preparing numerical and graphical summaries (visualizations).
Job requirements

The ideal candidate will have a background in Computer Science, Data Science, Bioinformatics or equivalent, with work experience in Machine Learning and programming and a deep knowledge of methods and tools for big-data analytics and management. S(he) should have an understanding or interest in learning population genetics concepts linking disease-associated genetic variants to function, and passion about using machine learning approaches for population genetic inference.

S(he) should have an open mind and creative approach to problem-solving, and be motivated by learning the genetic contribution of molecular phenotypes to complex diseases ultimately important for developing effective therapies.

Essential

  • Relevant degree (e.g. PhD or Master of Science in a relevant subject, e.g. Computer Science, Computational Biology, Statistics, Mathematics or a related field of Science);
  • Proven experience (scientific publications, github page or equivalent work experience) in performing analyses using machine learning classifier algorithms;
  • Experience of statistical or other programming languages (preferably R) to manipulate large-scale datasets with genetic/molecular information (excellent data management and analysis skills);
  • Fluency in English – HT is an international research institute.

Advantageous

  • Experience working with Genomic Data from different Modalities (DNA sequencing, RNA-seq, proteomics, DNA accessibility assays, etc.)
  • Experience in a HPC environment.

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. 

Application Instructions:

  • CV 
  • A  motivation letter in English
  • Names and contacts of 2 referees

For specific enquires concerning the role only, please contact Emanuele Di Angelantonio: emanuele.diangelantonio@fht.org (this email address should not be used to send applications). 

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 recognized status entitled to protection under applicable laws.
HT offers attractive conditions and benefits appropriate to a leading, internationally competitive, research organization that promotes a collegial and open atmosphere. The compensation package granted will be internationally competitive and comprise 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. 

Number of positions offered: 1

Contract offered: CCNL Chimico Farmaceutico, fixed-term, Employee level

Location: Milan - Italy
Salary: Not Specified
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 1st December 2022
Closes: 8th January 2023
 
   
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