Doctoral Student within biotechnology focusing on proteomics


Application deadline

November 21, 2022

Doctoral Student within biotechnology focusing on proteomics

School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH

KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.

Project description

Third-cycle subject: Biotechnology
 – Focus on Data-driven precision medicine and diagnostics

The subject concerns data-driven research on proteomics-based precision medicine and developing protein-based diagnostic computational tools.  The student will employ data-driven methods to integrate molecular and clinical data in order to facilitate translational research with an emphasis on diagnostic applications.

The primary role will be to conduct research within data-driven life science projects at Scilifelab. The primary goal of the Ph.D. student will be to examine proteomics datasets and construct AI models and/or other modeling methodologies in order to establish more precise and accurate protein quantification approaches. To enhance models for protein quantification in clinical samples, the PhD student will apply Data Independent Acquisition techniques in conjunction with stable isotope-labeled standards. Sample datasets from thousands of patients have been generated experimentally and are ready to be compiled and evaluated. Senior researchers from the division of Systems Biology, Department of Protein Science, will mentor the PhD student. The position includes teaching and other departmental responsibilities.

Supervision: Fredrik Edfors is proposed to supervise the doctoral student. Decisions are made on admission

What we offer

Admission requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

  • passed a second cycle degree (for example a master’s degree), or
  • completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
  • acquired, in some other way within or outside the country, substantially equivalent knowledge
  • To qualify as a Ph.D. student in this project, you must hold a master’s degree in a relevant field, namely biotechnology, bioinformatics or computer science (or similar)
  • It is important that you have solid programming skills for handling biological big data analysis
  • Ability to use Python and R with knowledge of data architectures and data pipelines
  • Knowledge in biostatistics modeling and machine learning
  • Knowledge in biological data management and data repository
  • Experience in handling chromatographic data from mass spectrometry, such as proteomics and/or metabolomics
  • Experience in using object-oriented programming in biological data
  • Experience in interpretable methods in AI, as well as AI applications in healthcare
  • Experience in using version control and public repository

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here


In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

  • independently pursue his or her work
  • collaborate with others,
  • have a professional approach and
  • analyse and work with complex issues.

After the qualification requirements, great emphasis will be placed on personal competency. 

Target degree: Doctor´s Degree

Last updated: 2022-11-16

Content Responsible: David Gotthold(