Position Information

Position Information Message
Post doctoral fellow in uncertainty in scientific assesments
Postdoc at Lund University Sweden working in an interdisciplinary project on the characterisation of uncertainty in scientific assessments with applications on human health risk assessment.

Full information can be found here https://lu.varbi.com/en/what:job/jobID:541436/

The postdoc will work with integrating data and evidence into models using computational modelling, including statistical modelling and machine learning, combined with expert knowledge elicitation to assess uncertainty in conclusions of an assessment. Specific focus is on uncertainties associated with new approach methodologies (NAMs) and Adverse Outcome Pathways (AOPs) used for chemical safety assessment as part of the RISK-HUNT3R project. The candidate will be involved in conceptualisation and applications of uncertainty characterisation in case studies defined within the project. This is a multi-disciplinary project involving statistical modelling and risk assessment, in collaboration with researchers in other disciplines, such as toxicology and molecular biology as well as computational science, statistics and risk analysis.

Apply before September 30th 2022
Position: Post doctoral fellow in uncertainty in scientific assesments
Organization: Lund University
Location: Lund,  OR 
Sweden
Salary:
Posting Start Date: 9/30/2022
Date Posted: 9/14/2022
Requirements Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

  • Very good oral and written proficiency in English
  • A higher education in mathematics and statistics or similar, with experience in Bayesian modelling

We are looking for a candidate interested in using subjective probability to quantify uncertainty. There will be learning opportunities in principles and methods for expert knowledge elicitation, Bayesian modelling (including generalisations thereof) and chemical safety assessment.

Status: This listing expires on: 10/14/2022
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Organization Information
Name:
Lund University
Address:


Lund,  OR 223 62
Sweden
Email:
ullrika.sahlin@cec.lu.se
Phone:
Fax:
Contact:
Ullrika Sahlin

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