Thesis work: CFD simulation to predict deposition, Gothenburg

Randstad AB / Matematikerjobb / Mölndal
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Job description
Thesis work: CFD simulation to predict the deposition of inhaled medicines in human lungs

If you're inspired by the possibilities of science to make a difference and ready to discover what you can do - join us!

Thesis type: 30 credits
Project start: January 2023
Student location: On Site, Gothenburg Sweden

A unique opportunity for a master thesis

Are you currently pursuing a master's degree with a burning interest in pharmaceutical development and computation fluid dynamics? This master's thesis project at AstraZeneca might be of interest to you!

At AstraZeneca Gothenburg, one of the focus areas is to develop medicines for the treatment of respiratory diseases e.g. asthma, COPD using pulmonary drug delivery technology. For this route, the deposition e.g. pattern and concentration, of drug particles at targeted areas in human lung is critical to the effectiveness of medicines.

The ultimate goal of this thesis is to investigate and quantitatively map the influence of critical attributes of medicines and patient profiles to drug deposition.

At AstraZeneca, all of our employees make a difference to patients' lives every day. We operate in more than 100 countries around the world and are one of Sweden's most important export companies.

With more than 2,400 employees from 50 countries, the vibrant Gothenburg site helps to support the entire life-cycle of AstraZeneca medicines, from drug discovery and clinical trials, to global commercialisation and product maintenance. Gothenburg is one of AstraZeneca's three strategic, global R&D centres, alongside Cambridge and Gaithersburg, and plays a central role in our mission to deliver life-changing medicines to patients.

Responsibilities
This thesis aims to develop CFD models towards an alternative tool to in-vivo and in-vitro methods in order to predict local deposition of drug particles in human lung.

Responsibilities include:

Developing and optimising CFD models for lung deposition on a realistic 3D geometry of human lung
Parametric study of lung deposition using the developed CFD models
Validating simulation results with available experimental data

The work is to be conducted from January to June 2023, or as agreed with the student.

Qualifications
Essential Requirements
Interest in pharmaceutical development
Experience and interest in computational fluid dynamics
Solid understanding in transport phenomena and mathematical modelling
Excellent problem solving, communication skills
Pursuing a master's degree in a relevant engineering discipline

Desirable Requirements
Skills in computer programming e.g. C++, python

About the company
If you're inspired by the possibilities of science to make a difference and ready to discover what you can do - join us!

At AstraZeneca we are guided in our work by a strong set of values, and we're resetting expectations of what a bio-pharmaceutical company can be. By truly following the science, we pioneer new methods, new thinking and bring unexpected teams together. From scientists to sales, lab techs to legal, we're on a mission to turn ideas into life-changing medicines that transform lives. We need great people who share our passion for science and have the drive and determination to meet the unmet needs of patients around the world. If you're swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.

AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law. AstraZeneca only employs individuals with the right to work in the country/ies where the role is advertised.

Varaktighet, arbetstid
Full time Contract

Publiceringsdatum
2022-11-16

Ersättning
Not specified

Så ansöker du
Sista dag att ansöka är 2022-12-02
Klicka på denna länk för att göra din ansökan

Företag
Randstad AB

Arbetsgivarens referens
Arbetsgivarens referens för detta jobb är "201416223".

Omfattning
Detta är ett heltidsjobb.

Arbetsgivare
Randstad AB (org.nr 556242-1718)

Arbetsplats
Randstad

Kontakt
Malin Fridholm
malin.fridholm@randstad.se

Jobbnummer
7178189

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