Industrial PhD student in cardiovascular research and computational image analysis

We are looking for a PhD student to join a collaborative research project between Gubra and the Department of Cardiology, University of Copenhagen. The project is supported and funded by the Innovation Fund Denmark. As a PhD student you will contribute to image analysis development, establishing objective and automated workflows for the characterization of cardiac function in preclinical models and demonstrating how key parameters correlate between heart failure models and patients. 


Gubra is an ambitious biotech company striving for excellence at all levels. We insist on doing things efficiently – and often differently – to reach the results we aim for. Our vision is to become leaders in the fight for a more sustainable and healthier world. We do this by facilitating the discovery of new medicines, and by acting and inspiring others to fight against the ongoing climate and biodiversity crisis. 
The PhD student will be placed within the Department of Computational Biology at Gubra. There will be extensive collaborations between other departments within Gubra. At Gubra we use echocardiography and cardiac strain analysis to study how novel drug candidates affect cardiac function in mouse models of human diseases. We also have world-leading 3D light sheet imaging facility to visualize cellular and molecular changes in cleared tissues and organs. We use the combination of in vivo readouts and light sheet imaging for external contract research as well as internal drug discovery projects.  

The student will also be introduced to the analysis of cardiac function in humans as the project collaborate with researchers at Department of Biomedical Sciences, Faculty of Health and Medical Sciences and Cardiovascular Non-Invasive Imaging Research Laboratory at the Department of Cardiology, University of Copenhagen. 


PhD project aims

  • Development of automated image analysis workflows for characterizing echocardiography and cardiac strain data from mouse heart failure models 

  • Development of an automated image analysis workflow for 3D light sheet microscopy data from relevant heart models 

  • In internal collaboration, validating the developed image analysis methods in preclinical pharmacology studies 

  • Using imaging data, demonstrating how structural changes in heart failure contribute to impaired cardiac function 

  • Establishing the translatability of key functional parameters between rodent models and heart failure patients 

  • The student will be introduced to preclinical pharmacological research and will be included in well-established PhD student program at Gubra. 

  • The student is expected to publish the findings in scientific journals and present the results at high level international conferences  

  • She/he will also be introduced to the basics of clinical imaging of cardiac function in patients 

Your competencies:  

  • MSc degree within a life science, computational, biomedical, or other relevant area. 

  • Interest and experience in quantitative image analysis, covering both classical as well as deep learning-based approaches 

  • A strong background in writing code (Python preferred). 

  • Experience working on Linux servers 

  • Experience in scientific writing 

  • Experience in scientific data presentation and visualization 

  • Interest in broad range of preclinical and clinical imaging modalities 

As a person you:   

  • Are driven by a collaborative and innovative mindset. 

  • Are self-motivated and keen to take on responsibility. 

  • Are proactive and takes responsibility for the project 

  • Have eye for detail. 


The project is supported by the Innovation Fund Denmark and funding is available. Please note that PhD candidate must meet the criteria described by the Innovation Fund Denmark. The criteria are available the from Guidelines: Industrial PhD chapter 1.6 (LINK). The weighted grade point average can be calculated using the Calculation sheet, industrial PhD [XLS] which is available for downloaded at the Innovation Fund Denmark homepage (LINK).    

Please apply no later than May 31st 2022 by uploading your motivated cover letter and resume on our website. Furthermore, please fill out and upload the excel file “Calculation sheet, industrial PhD [XLS] (see above) as part of the application. 

Please note that applications will be reviewed on an ongoing basis.  

If you have questions about the position, please contact: Martin Mikkelsen, Department manager, 

About Gubra  
Gubra is a company with a very dynamic and fast-paced drive. We have two primary areas of business: Preclinical contract research (CRO) services, and Proprietary early target and drug discovery programs.  
We are a biotech company delivering science to our partners and to our own research projects. We are active in the so-called pre-clinical space - before drugs are tested in humans - and generate a revenue by performing research for small and large pharma companies.   
Our focus is within the metabolic space (obesity, diabetes, NASH, and diabetic complications), where we specialize in in vivo pharmacology, peptide chemistry, molecular pharmacology, histology, stereology, imaging, NGS (next generation sequencing), bioinformatics and assays. We work with some of the most interesting and loyal partners and customers from across the world within big pharma, biotech, and academia. Through a constant focus on high quality, scientific excellence, speed, and solid teamwork we have established ourselves as a highly professional and competent partner in the market. 
People are our greatest asset, and our team consists of +170 employees all located in Hørsholm, Denmark. The mix of people from different cultures and educational backgrounds combined with our entrepreneurial mindset have greatly impacted our working environment, which is characterized by intensive drive, scientific curiosity, and teamwork – we join forces! 


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Contact person:
Martin Mikkelsen Department Manager, Computational Biology
Job area: Computational Biology
Employment terms: Full time
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