Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Scientific Meetings
PSI Training Course: Simulation of Clinical Trials using Tidyverse
Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Training Courses
PSI Training Course: Simulation of Clinical Trials using Tidyverse
Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Journal Club
PSI Training Course: Simulation of Clinical Trials using Tidyverse
Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Webinars
PSI Training Course: Simulation of Clinical Trials using Tidyverse
Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Careers Meetings
PSI Training Course: Simulation of Clinical Trials using Tidyverse
Date: Monday 14th March - Thursday 7th April 2022 Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00 Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail. Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics. What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
Course Cost
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February. Early Bird Members = £320+VAT Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
Dates & Times
All sessions will be run online via Zoom. Main presentation sessions: Session 1 - Monday 14th March, 09:30-12:30 GMT Session 2 - Monday 21st March, 10:00-12:00 GMT Session 3 - Monday 28th March, 10:00-12:00 BST* Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions: Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST* Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
Speaker details
Speaker
Biography
Matt Neilson
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021.
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Upcoming Events
PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities
This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation.
The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication.
The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication.
The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This webinar brings together three bitesize complementary sessions to help PSI contributors create conference presentations and posters that communicate clearly and inclusively. Participants will explore how to refine their message, prepare materials effectively, and adopt practical habits that support confident, accessible delivery. A focused, supportive session designed to elevate every contribution.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
Join our Health Technology Assessment (HTA) European Special Interest Group (ESIG) for a webinar on the strategic role of statisticians in the Joint Clinical Assessment (JCA). The introduction of the JCA marks a new era for evidence generation and market access in Europe. As HTA requirements become more harmonized and methodologically demanding, the role of statisticians has evolved far beyond data analysis. Today, statistical expertise is central to shaping clinical development strategies, designing robust comparative evidence, and ensuring that submissions withstand the scrutiny of EU-level assessors. In this webinar, we explore how statisticians contribute strategically to successful JCA outcomes.
Statisticians in the Age of AI: On Route to Strategic Partnership
A 90-minute webinar featuring two case studies from Bayer and Roche demonstrating how statisticians successfully integrated into AI programs, followed by interactive discussion on strategies for elevating statistical expertise in the AI era.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
GSK - Statistics Director - Vaccines and Infectious Disease
We are seeking an experienced and visionary Statistics Director to join our Team and lead strategic statistical innovation across GSK’s Vaccines and Infectious Disease portfolio.
As a Senior Biostatistician I at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
As a Statistical Scientist at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
We have an exciting opportunity for an Associate Director, Biostatistics to join a passionate team within Advanced Quantitative Sciences – Full Development.
: We have an exciting opportunity for an Associate Director (AD), Statistical Programming, to join a passionate team within Advanced Quantitative Sciences- Development.
Novartis - Senior Principal Statistical Programmer
We have an exciting opportunity for a Senior Principal Statistical Programmer, to join a passionate team within Advanced Quantitative Sciences – Development.
Pierre Fabre - Clinical Development Safety Statistics Expert M/F
We are seeking a highly skilled and proactive Clinical Development Safety Statistics Expert to join our Biometry Department and the Biometry Leadership Team based in Toulouse (31, Oncopole) or Boulogne (92).
Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
Pierre Fabre Laboratories are hiring a highly skilled and experienced Lead Statistician – Real World Evidence (RWE) to join the Biometry Department, part of the Data Science & Biometry Department, based in Toulouse (Oncopôle) or Boulogne.
Pierre Fabre - Lead Statistician- Clinical Trials M/F
We are seeking a highly skilled and experienced Lead Statistician in Clinical Trials to join our Biometry Department based in Toulouse (31, Oncopole) or Boulogne (92).
We are looking for Senior Statistical Programmers in the UK to join Veramed, where you'll deliver high-impact programming solutions in an FSP-style capacity, while advancing your career in a supportive, growth-driven environment.
