With operations in 35+ nations and ~ 22,000 employees worldwide, CSL is driven to develop and deliver a broad range of lifesaving therapies to treat disorders such as hemophilia and primary immune deficiencies, and vaccines to prevent influenza. Our therapies are also used in cardiac surgery, organ transplantation and burn treatment.
CSL is the parent company of CSL Behring and Seqirus. CSL Behring is a global leader in the protein biotherapeutics industry, focused on bringing to market biotherapies used to treat serious and often rare conditions. CSL Behring operates CSL Plasma , one of the world's largest collectors of human plasma, which is used to create CSL’s therapies. Seqirus is the second largest influenza vaccine company in the world and is a transcontinental partner in pandemic preparedness and a major contributor to the prevention and control of influenza globally.
We invite you to take a look at the many career possibilities available around the globe and consider building your promising future at CSL by becoming a member of our team!
This Internship will be undertaken by a PhD candidate in the field of pharmacometrics, clinical pharmacology, or translational medicine at a leading academic institution. The purpose of the Internship is to enable PhD students to gain hands-on experience with pharmaceutical industry data, to forge links between CSL Behring (CSLB) and leading academia, and to enable CSLB’s Clinical Pharmacology and Pharmacometrics (CPP) function to progress non-critical R&D program work which often gets sidelined due to portfolio priorities.
This Internship will not be formally associated with any academic institution (i.e., in any accreditation sense or university Agreement). The intern will be based within the CPP group at CSLB, King of Prussia, PA (USA) on full-time basis (40 hours per week) for 10-12 weeks duration. Candidates for this role should be in the advanced stages of a PhD program involving quantitative analyses of biological systems. Prior industry experience will not be required. Experience with modeling and/or statistical software is preferred (e.g. Phoenix, NONMEM, R/R Shiny, Matlab).
By the end of the Internship, the student should have gained an insight into (a) the nature of pharmacometric and translational data generated within industry, (b) the processes and systems involved in data analyses, (c) analytical and clinical decision making related to pharmacometric conduct, and (d) functioning of matrix teams. With strict internal agreement by relevant functions at CSLB, there may be a possibility for the student to submit the work as an abstract to Clinical Pharmacology/ Pharmacometrics Scientific Society and include some of their Internship pharmacometric work into their PhD dissertation.