<p> Pharmacometrics / Applied Statistics / Mathematical Modelling (18 months fixed term contract) </p><p>Division of Clinical Pharmacology DEPARTMENT OF MEDICINE FACULTY OF HEALTH SCIENCES</p><p>The Worldwide Antimalarial Resistance Network (WWARN) is a global collaboration working to collate and share comprehensive, timely and quality-assured intelligence to track the emergence of antimalarial drug resistance (www.wwarn.org). Achieving adequate antimalarial drug concentrations in the blood is pivotal to curing malaria. The WWARN Pharmacology Module is based in the Division of Clinical Pharmacology of the University of Cape Town’s Department of Medicine with strong links with its many international partners. The objectives of the statistical modelling within the WWARN Clinical Pharmacology module are to determine the effect the drug concentration profiles have on treatment response (i.e. pharmacodynamic measures), patient factors that influence drug concentration over time profiles (i.e. pharmacokinetic profiles), and the implications of these pharmacokinetic-pharmacodynamic relationships for antimalarial dosing in key target population groups. The successful candidate will report to the WWARN Clinical Pharmacology module director (UCT) and WWARN Head of Statistics (UK), with linkage to the WWARN Pharmacology Scientific Coordinator (UCT) and IT team manager (UK), as well as our international network of WWARN data contributors.</p><p>Requirements include: Essential:  A PhD in pharmacometrics, applied statistics or mathematical modelling (or a closely related field)  Evidence of strong academic capacity in the form of publications or other scientific research output with high statistical contents in relevant areas  For appointment as senior lecturer, at least 3 years post-doctoral experience in pharmacometrics / applied statistics / mathematical modelling  Experience in data management and analysis of large databases  Good communication and presentation skills, both oral and written  The ability to work both independently and as a member of a team  The ability to work against tight deadlines  Self-motivation. Advantageous:  Fluency in statistical / pharmacometric software, including Stata,S-Plus/R, WinNonLin, MONOLIX, NONMEM and BUGS/WinBUGS.  Experience with nonlinear mixed effects modeling and / or model-based meta-analysis.  Experience in infectious diseases (preferably malaria) and clinical pharmacology research.</p><p>Responsibilities include:  Statistical analysis: Summarising, analysis and graphical representation of pharmacokinetic (PK) and pharmacodynamic (PD) data contributed to WWARN for online visualization on WWARN explorer.  Population PK-PD analysis: Modelling of pooled individual patient pharmacokinetic (PK) and pharmacodynamic (PD) data contributed to WWARN.  Contribute to the searchable database of published antimalarial pharmacokinetic research.  Contribute to capacity building of the statisticians and pharmacometricians analysing data contributed to WWARN.  Initiating and strengthening collaborations with existing and potential WWARN Pharmacology data contributors.</p><p>The annual remuneration package is negotiable between R443 436 and R544 187.</p><p>Application process: To apply, please e-mail the completed UCT Application form (download at http://web.uct.ac.za/depts/sapweb/forms/hr201.doc) and all other relevant documentation as indicated on the form, to Mrs Marilyn Solomons, Division of Clinical Pharmacology, Department Medicine, Old Main Building, Groote Schuur Hospital, Anzio Road, Observatory.</p><p>Email: [email protected] ; Tel: 021 4066779; Website: www.medicine.uct.ac.za </p><p>An application which does not comply with the above requirements will be regarded as incomplete. </p><p>Reference number for this position: 2325</p><p>Closing date for applications: 5 September 2011</p><p>UCT is committed to the pursuit of excellence, diversity and redress. Our Employment Equity Policy is available at http://hr.uct.ac.za/policies/ee.php. </p><p>04ea6b48aa5f8a2531bd974e55bcd6a3.doc 6/2/2018 10:22 AM</p>