The ISBA Biostatistics and Pharmaceutical Statistics Section is pleased to call for submissions for the 2024 ISBA Biostats and Pharma Junior Researcher Award, and the 2024 ISBA Biostats and Pharma Best Paper Award. The deadline for submissions is June 30, 2024. Please prepare nominations as a single pdf file following the convention LASTNAME_FIRSTNAME.pdf so the file name corresponds to the nominee and then email them to isba.biostatspharma@gmail.com, provided the file is less than 25MB. For files larger than 25MB, please contact Valerie Poynor at vpoynor@fullerton.edu to make appropriate alternative arrangements. For further details about rules and eligibility, please visit https://isba-biostatspharma.github.io/ for more information.
2024 ISBA Biostats and Pharma Junior Researcher Award
The ISBA Biostats and Pharma Junior Researcher Award is to be awarded to a student or early career researcher who has made important original contributions to either the foundations, theoretical developments, and/or general methodology of Bayesian analysis in the field of biostatistics or pharmaceutical statistics, or that has solved a substantive applied problem that has potential to impact statistical practice in the biological and pharmaceutical sciences.
2024 ISBA Biostats and Pharma Best Paper Award
The ISBA Biostats and Pharma Best Paper Award is bestowed upon an individual or individuals based on their innovative use of Bayesian statistics to solve a high-impact problem in the biostatistical and pharmaceutical sciences.
In even numbered years, the award is presented for a paper published in a refereed journal that presents distinguished work performed by a collaborative team of statisticians and practitioners with regards to an application of Bayesian methods to an applied problem in the biological and pharmaceutical sciences. In odd numbered years, the award is presented for a paper published in a refereed journal that makes important original contributions to the foundations, theoretical developments, and/or general methodology of Bayesian analysis in the biostatistical and pharmaceutical sciences.