Postdoc Position at University of Florence

ManpowerGroup; Remoto; EUR 30.000 - 38.000; Tempo pieno

Descrizione del lavoro

A leading research institution is seeking a Postdoc for a project focused on Bayesian Methods for Clinical Studies. This position offers a salary of EUR 30,000 - 38,000, remote work options, and a duration of 16 months. Candidates must have a Ph.D. and a non-Italian affiliation for at least 24 months in the past three years. Interested applicants should send their CV to the provided contact email before the September 10, 2023 deadline.

Competenze

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

Mansioni

• Develop Bayesian Methods for Clinical and Observational Studies.
• Speed up the drug development process.
• Increase power of results and biomarker discovery.

Formazione

Ph.D.

Descrizione del lavoro

Postdoc Position at University of Florence

EUR 30,000 - 38,000

Start: October 1, 2023; Duration: 16 months; Location: Department of Statistics, Computer Science, Application, University of Florence (remote work allowed, occasional presence required).

Deadline: September 10, 2023.

Interview will be arranged after application – to be agreed.

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

Project title: Bayesian Methods for Clinical and Observational Studies.

Abstract: Traditional development of new drugs and biomarkers has followed the “one drug, one target disease” strategy, which is costly and inefficient and often leads to failure. Contrary to this strategy, we aim to create Bayesian Methods for Clinical and Observational Studies that study heterogeneous populations, target several diseases, and test various treatments from the pre‑clinical and clinical stages. The aim of the project is to speed up the drug development process while increasing the power of results and biomarker discovery using adaptive randomization. We will develop novel and ethical Bayesian adaptive designs that: integrate data coming from non‑concurrent trials; change the randomization ratios using covariate‑dependent models; provide a way to analyze the study in the presence of intercurrent events, i.e., events that take place after the randomization and may bias the study results, in a causal framework.

Keywords: adaptive trials, causal inference, precision medicine.

Contact: Send a CV to [e-mail].