similar to: Vacancy - PhD / Post-doctoral position at the University of Leiden.

Post-Doctoral Fellowship Modelling of Cardiovascular Safety (full time) Leiden University, Leiden, The Netherlands <javascript:doredirect();> Job description TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PKPD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a

Two Postdoctoral fellows (fulltime) Leiden University, Leiden, The Netherlands Job description ________________________________________ TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PK-PD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a collaborative effort of

________________________________ Principal Post-Doctoral Fellow PKPD modelling platform (full time) Leiden University, Leiden, The Netherlands <javascript:doredirect();> Job description ________________________________ TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PK-PD modelling platform. This platform focuses on the transfer of

Dear all, Should you be interested in a career at our mechanism-based PK-PD modeling platform, please read the remainder of this message. Best wishes, Margot Beukers Unique PK-PD modeling platform established in The Netherlands Are you our ambitious IT platform manager with a profound drive to contribute to a new era of drug research? PK-PD modeling platform Prof. dr.

Vacancy number 300014 LECTURER Department of Statistics School of Computing and Mathematical Sciences University of Waikato Hamilton, New Zealand You should have a PhD in Statistics, or equivalent, and will have demonstrated the ability to sustain a successful teaching and research career. You will be expected to contribute towards the Department?s undergraduate and graduate teaching

I am trying to use the survfit() function with the newdata argument to produce predicted survivor curves for a particular covariate profile. The main purpose of the plot will be to visualise the effect of snp1, coded 0 and 1. In my Cox model I have stratified by one variable, edu, and so I know I will automatically get a separate curve for each strata. My problem is how to deal with the

Dear R users, I am curious to know if someone has connected R with the Insight Segmentation and Registration Toolkit (www.itk.org). From the website... ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and

R-help, I am trying to perform a basic anlaysis of the BreastCancer data from "mlbench" using the svm() function in "e1071". I use the following code library("e1071") library("mlbench") data(BreastCancer) BC <- subset(BreastCancer, select=-Id) pairs(BC) model <- svm(Class ~ ., data=BC, cross=10) ## plot(model, BC, ) tobj <- tune.svm(Class ~ .,

dcemri 0.10 has been released on CRAN "dcemri" is (to the best of my knowledge) the first public-domain software package for the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI or DWI). Data import and export is availble for ANALYZE or NIfTI data formats (sorry, no DICOM). Images are stored in neurological format regardless of the

dcemri 0.10 has been released on CRAN "dcemri" is (to the best of my knowledge) the first public-domain software package for the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI or DWI). Data import and export is availble for ANALYZE or NIfTI data formats (sorry, no DICOM). Images are stored in neurological format regardless of the

Hello all, Currently we are looking at the possibility of moving from Courier-IMAP to Dovecot (the one that comes with Debian Lenny: version 1.0.15). I'm currently testing it on a non-production server and have a few questions: 1) Currently all our clients use Thunderbird as their mail client to read mail from our IMAP server. Thunderbird is configured with "INBOX." as the

Dear all, I have two questions: 1. Does anyone know if nlmeODE package will work once odesolve is discontinued? If i understand well nlmeODE depends on odesolve. 2. Can anyone suggest another package I could use to fit complex PKPD models (described using differential equations) to data? Thanks a lot! Magdalena

Hey everyone, I've searched through the archives and can find mention of the problem, but haven't been able to track down an answer. The problem is as follows, certain accounts can't login to the samba PDC server (can't login to the domain, check your password error), while other accounts can. The mystery becomes completely baffling to me when I look at the more recent PC's in

*Vacancy: Scientific Collaborator in Statistical Bioinformatics* *Institute for Medical Informatics, Statistics and Documentation**, Medical University of Graz, Austria* predoc level with PhD opportunity, 30 hours per week available from May 1st, 2012 *Tasks:* * Working in the project "Biostatistical-genomical analysis of the clinical relevance of liver cancer models" which is

I'm using the 'pnt' C function from Rmath library in some C-code. How can I catch the warning message: "full precision was not achieved in 'pnt'" in R. I call the function using the .C(). (options(warn=-1) didn't work) Thanks in advance -- Maarten van Iterson Center for Human and Clinical Genetics Leiden University Medical Center (LUMC) Research Building,

I use model comparison with glms without mixed effects with anova(modelA,modelB), with mixed effects glm (glmmPQL), this doesn't work. Is there a way to compare model fits with glmmPQL's? Paula M. den Hartog Behavioural Biology Institute of Biology Leiden Leiden University [[alternative HTML version deleted]]

Dear list, If have some repeated measurement data which looks something like: time <- rep(1:5 , each=2*4) groups <- rep(c("Case", "Control"), each=4) subjects <- factor(rep(1:(2*4), 5)) responses <- time + rnorm(5*2*4) + as.integer(factor(groups)) data <- data.frame(responses, time, groups, subjects) Now I want to plot each subject in a separate panel:

Dear all, I would like to use predict.lm() with an existing lm object but with new arbitrary coefficients. I modify 'fit$coef' (see example below) "by hand" but the actual model in 'fit' used for prediction does not seem to be altered (although fit$coef is!). Can anyone please help me do this properly? Thanks in advance, J?r?mie > dat <-

Hi, there: As you all know, correlation is not a very robust procedure. Sometimes correlation could be driven by a few outliers. There are a few ways to improve the robustness of correlation (pearson correlation), either by outlier removal procedure, or resampling technique. I am wondering if there is any R package or R code that have incorporated outlier removal or resampling procedure in

The Statistics & Decision Sciences community at Johnson & Johnson is searching for individuals to help in the mission of discovering, developing, manufacturing, and delivering beneficial medicines for patients. The group resides within the Janssen R&D organization in Johnson & Johnson's pharmaceutical segment. We need individuals with skills and motivation to consistently and