Postdoc in Machine Learning for Bioimage-Based Profiling

KTH Royal Institute of Technology, Scool of Electrical Engineering and Computer Science

Cellular morphology reflects fundamental biological processes such as division, differentiation, stress response, and apoptosis, yet it remains unclear whether these processes follow conserved organizational principles across cell types and experimental systems. Large-scale fluorescence microscopy datasets now capture millions of single-cell images across diverse perturbations, but differences in imaging protocols, marker panels, and cell types limit their integration and reuse. A key challenge is therefore to determine whether shared biological structure can be recovered across heterogeneous datasets or whether morphology is dominated by context-specific variation.

The MirandaLab is recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches. The project focuses on developing novel representation learning and generative modeling methods to construct a unified cellular morphology state space across heterogeneous datasets. By leveraging shared biological markers and state-of-the-art deep learning, the research will uncover conserved cellular state transitions and perturbation response programs across biological systems.

The successful candidate will join a highly interdisciplinary and collaborative research environment within the Department of Computational Science and Technology, working closely with researchers at SciLifeLab and international collaborators in computational biology, machine learning, and imaging-based profiling. The position involves leading independent research projects at the interface of machine learning and biology, with a strong emphasis on method development, large-scale data integration, and biological discovery.

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• Substantial research expertise in the field of image-based profiling and computational biology methods for single-cell or tissue data.
• Extensive knowledge of relevant machine learning and AI techniques
• Proven scientific excellence as evidenced by strong scientific publications and track record relative to career stage
• Strong programming skills (Python or R) and familiarity with high-performance computing

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• Highly creative researcher with broad scientific curiosity
• Exceptional collaborative abilities
• Self-motivated individual with the ability to work independently
• Teaching and mentorship abilities or interests in personal development
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Great emphasis will be placed on personal skills.

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Log into KTH’s recruitment system to apply for this position. You are responsible for ensuring that your application is complete according to the instructions in the ad.

The application must include:

• CV including relevant professional experience and knowledge.
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
• Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Maximally two pages long.

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

The position offered is for, at the most, two years.

A position as a postdoctoral fellow  is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.

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