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Post-doctoral Data Scientist Fairness in machine learning for health

Vacancy number
Academic staff, PhD positions
Internal , External
Publication date
14 March 2023
Closing date
14 April 2023 Vacancy closed

The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a :

Post-doctoral Data Scientist Fairness in machine learning for health
Vacancy number: 23-181

Do you want to contribute to a promising start for children growing up in difficult conditions? This project will apply state of the art machine learning techniques to identify risk and protective factors in a unique nation-wide dataset. These factors can subsequently support timely tailored interventions and preventive policies.

Making big data meaningful for a promising start
All children deserve a promising start. Most children are doing fine. But some need extra support, because of problems during pregnancy or because they grow up in disadvantaged circumstances, e.g., due to poverty, parental addictions, or psychological problems. In this  multidisciplinary NWA funded project, we will investigate how relevant register datasets, collected and/or hosted by Statistics Netherlands (CBS), can be used to support these children and (expectant) parents. Predictive risk models based on statistics and machine learning will be used to enable more timely referral to services that meet their needs and to tailor municipal policies to the needs of vulnerable children and (expectant) parents.  We collaborate with parents, practitioners, and municipalities to ensure our research meets their priorities. This collaborative project includes partners from the Department of Public Health (Erasmus MC), the Departments of Psychiatry and Child and Adolescent Psychiatry and Psychology (Erasmus MC), the Leiden Institute of Advanced Computer Science, the City of Rotterdam, and a broad range of societal partners.

Key responsibilities
You will be the researcher responsible to translate the current high-level guidelines for trustworthy AI into practice for the use of big data for risk prediction at family and population level, for the purpose of screening and municipal health policy making.  Working in the secure environment of Statistics Netherlands, you will develop methods to identify potential bias, risk for stigmatization, discrimination in the data and in the analysis pipeline. You also develop strategies to mitigate these and maximize transparency and explain ability in accordance with national and EU legislation and policies regarding application of AI in sensitive settings.

You collaborate in a team both locally (Postdoc predictive risk modelling) as well as with the post-docs for this project that are based at the Departments of Public Health, Psychiatry and Child and Adolescent Psychiatry and Psychology (Erasmus MC). You will publish your results in international peer-reviewed journals. Relevant data science challenges include:
•    Handling missing data;
•    Measuring and modelling fairness;
•    Mitigating bias;
•    Explainable models;
•    Incorporating prior knowledge in predictive models.

Selection Criteria
The ideal candidate can work independently, but also enjoys working in a team and in accordance with the project goals. You have a thorough understanding of state-of-the-art Data Science research methods and have significant experience with data analysis and machine learning using R and/or Python. To be successful you have:
•    A PhD degree in Data Science, Computer Science, Statistical Science, Social Sciences or Epidemiology with a strong focus on data intensive research methods;
•    Excellent skills in spoken and written English are required. Fluency in Dutch is an asset (research data and tools are Dutch), but not a condition.
•    Experience with the Statistics Netherlands (CBS) research environment is a plus.
•    Proven affinity for (population) health research and/or fairness in AI is a plus.

The research position will be embedded in the health data science group which is also linked to the Population Health Living Lab of LUMC. The environment will offer plenty opportunities for interdisciplinary data science research and collaboration with postdoctoral researchers at Erasmus MC, LIACS and professional stakeholders.

Research at our faculty
The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our people are committed to expand fundamental knowledge by curiosity and to look beyond the borders of their own discipline; their aim is to benefit science, and to make a contribution to addressing the major societal challenges of the future. 
The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The research activities are organized in eight institutes. These institutes offer eight bachelor’s and twelve master’s programmes. The faculty has grown strongly in recent years and now has more than 2.300 staff and almost 5,000 students. We are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information, see https://www.universiteitleiden.nl/en/science and https://workingat.leiden.edu/ 

Terms and conditions  
The position is open until filled. We offer a 1.0 fte position for 15 months. You will be appointed in accordance with the Collective Labour Agreement for Dutch Universities. The salary ranges from 
€ 2.960,- to € 4.670,-  gross per month (at 1.0 fte), depending on experience (pay scale 10 VSNU).

Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3 %), training and career development. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. For international spouses we have set up a dual career programme. Candidates from outside the Netherlands may be eligible for a substantial tax break. For more information, see the website.

All our PhD students are embedded in the Leiden University Graduate School of Science https://www.graduateschools.leidenuniv.nl 

Our graduate school offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the SIKS PhD research school ( https://siks.nl/ )

D&I statement
Diversity and inclusion are core values of Leiden University. Leiden University is committed to becoming an inclusive community which enables all students and staff to feel valued and respected and to develop their full potential. Diversity in experiences and perspectives enriches our teaching and strengthens our research. High quality teaching and research is inclusive.

Enquiries can be made to Professor Wessel Kraaij, email w.kraaij@liacs.leidenuniv.nl If you have any questions about the procedure, please contact Anne-Marie Alleblas, email: jobs@liacs.leidenuniv.nl

Are you enthusiastic about this vacancy? We are looking forward getting to know you. Please send an 
e-mail to jobs@liacs.leidenuniv.nl The closing date is April 14th 2023, but promising early applicants may receive an immediate invitation for an interview. 

To apply for this vacancy, please send an email to jobs@liacs.leidenuniv.nl. Please ensure that you upload the following additional documents quoting the vacancy number:
•    Cover letter motivating your interest in this vacancy;
•    Full curriculum vitae, including a list of publications;
•    (Draft of) PhD Thesis;
•    Brief statement about your research ambition and past research;
•    Contact details of at least three persons who are prepared to provide a reference     

Only applications received before April 14th 2023, 23:59 CET can be considered.

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