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Doctoral student in Biological Systems at KTH Royal Institute of Technology, Sweden

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Summary

The School of Electrical Engineering and Computer Science at KTH invites applications for a Doctoral Student position focused on Deep Learning for Biological Systems. This role involves modeling cell-cell interactions aimed at disrupting cancer-promoting behaviors, contributing to advancements in precision medicine.

Doctoral student specializing in Deep Learning for Biological Systems at KTH Royal Institute of Technology in Stockholm, Sweden

Designation

Doctoral Student in Deep Learning for Biological Systems

Table of Contents

SectionDetails
Research AreaMachine Learning, Biological Systems, Cancer Research
LocationKTH Royal Institute of Technology, Stockholm, Sweden
Eligibility/QualificationMaster’s degree in relevant fields (e.g., Electrical Engineering, Mathematics) or equivalent qualifications.
Job DescriptionDevelop models and tools to understand and validate cell interactions, work with digital twins, and enhance drug development processes.
How to ApplySubmit your application through KTH’s recruitment system, including required documents as outlined below.
Last Date for ApplyJuly 31, 2026

Research Area

The project focuses on understanding and modeling biological interactions, especially in the context of cancer. The objective is to enhance precision medicine through innovative computational methods.

Location

KTH Royal Institute of Technology, Stockholm, Sweden

Eligibility/Qualification

  • A second cycle degree (Master’s) in Electrical Engineering, Computer Science, Mathematics, or a closely related field.
  • Minimum of 120 higher education credits at second-cycle level.
  • Proficiency in English equivalent to English B/6.
  • Desired qualifications include interest or experience in biological systems, research abilities, and experience with deep learning models.

Job Description

  • Conduct independent research focused on cell-cell interactions in cancer.
  • Develop in silico and in vitro models to create and validate digital twins.
  • Collaborate with researchers from institutions like AstraZeneca and SciLifeLab.
  • Contribute to advancements in drug development to reduce trial-and-error practices.

How to Apply

Interested candidates should ensure that their applications include:

  • Copies of diplomas and grades (with translations if necessary).
  • A CV detailing relevant experience.
  • An application letter (max 2 pages) discussing research interests and qualifications.
  • Representative publications or technical reports (with links for longer documents).
  • Contact information for at least three references.

Applications must be submitted through KTH’s recruitment system by the deadline.

Last Date to Apply

July 31, 2026


For more information, visit KTH DCS.

Link

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