Postdoc Position at University of Florence

The International Society for Bayesian Analysis; Venezia; Ibrido; EUR 30.000 - 45.000; Tempo pieno

Descrizione del lavoro

The Department of Statistics, Computer Science, and Application at the University of Florence offers a post-doctoral researcher position focusing on Bayesian Methods for Clinical and Observational Studies, allowing remote work. The project aims to enhance drug development through innovative Bayesian adaptive designs and involves analyzing heterogeneous populations over 16 months.

Competenze

• Ph.D. required in a related field.
• Non-Italian affiliation for at least 24 months in the last 3 years.

Mansioni

• Develop Bayesian methods for clinical and observational studies.
• Create Bayesian adaptive designs integrating data from non-concurrent trials.
• Analyze studies with intercurrent events within a causal framework.

Conoscenze

Bayesian Methods

Causal Inference

Adaptive Trials

Precision Medicine

Formazione

Ph.D.

Descrizione del lavoro

Postdoc Position at University of Florence

Aug 31, 2023

The Department of Statistics, Computer Science, and Application at the University of Florence is offering a post-doctoral researcher position in Bayesian Methods for Clinical and Observational Studies, starting on October 1st.

Location : Department of Statistics, Computer Science, and Application, University of Florence. Working remotely is allowed; occasional presence in Florence may be required.

Duration : 16 months

Deadline : September 10th

Interview : A few days after the application submission – to be scheduled.

Requirements : Ph.D. and a non-Italian affiliation for at least 24 months within the last 3 years.

Project title : Bayesian Methods for Clinical and Observational Studies

Abstract : Traditional drug development often follows a "one drug, one target disease" approach, which is costly and frequently unsuccessful. This project aims to develop Bayesian methods for clinical and observational studies that analyze heterogeneous populations, target multiple diseases, and test various treatments from pre-clinical to clinical stages. The goal is to accelerate drug development, enhance result power, and improve biomarker discovery through adaptive randomization. We will create novel Bayesian adaptive designs that integrate data from non-concurrent trials, adjust randomization ratios based on covariates, and analyze studies with intercurrent events within a causal framework.

Keywords : adaptive trials, causal inference, precision medicine

Contact : Send a CV to

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