The Molecular Programming group at KTH Royal Institute of Technology is recruiting two fully funded PhD students to work at the intersection of biotechnology, computation, physics, and machine learning.

Our group develops new technologies using DNA as an engineering material. We are interested in how concepts from computation, network science, and information theory can be translated into molecular systems for sensing, inference, and biological measurement. Research directions include DNA computing, sequencing-based microscopy, molecular networks, spatial transcriptomics, and chemical neural networks.

The positions are based at KTH and SciLifeLab in Stockholm, Sweden, in an interdisciplinary environment spanning molecular biology, DNA nanotechnology, genomics, machine learning, and applied mathematics.

Position 1: DNA-based chemical neural networks ("smart PCR")

This project develops molecular systems in which neural-network-like computation is implemented directly through DNA chemistry. The work combines molecular biology, thermodynamics, reaction network design, and computational modelling of DNA strand dynamics.

The broader goal is to develop programmable biochemical systems capable of recognizing patterns in molecular mixtures without sequencing or conventional digital computation.

Suitable backgrounds include biotechnology, molecular biology, biochemistry, engineering, biophysics, or DNA nanotechnology. Computational experience is beneficial.

Apply: Smart PCR PhD position
Applications accepted until the beginning of June.

Position 2: Spatial reconstruction from single-cell genomics

This project develops graph-theoretical and machine learning methods to recover spatial organization in tissues from single-cell RNA sequencing and molecular network data.

The work focuses on algorithm development, large-scale data analysis, and computational inference for spatial biology. This position is associated with the Swedish national Data-Driven Life Science (DDLS) program initiative.

Suitable backgrounds include applied mathematics, physics, computer science, computational biology, engineering, or related quantitative disciplines.

Apply: Computational spatial genomics PhD position
Applications accepted until the beginning of June.

We are always looking for potential Master's thesis students (year-round) who want to conduct their thesis with us and work as part of our team. Students from SciLifeLab, KTH, KI, or other Master's programs are welcome to inquire. Our aim is to develop novel biotechnologies that use the programmable information storage capabilities of DNA to create molecular logical circuits, control the interactions of molecules, define structures at the nanoscale, and gather information from biological specimens through DNA sequencing methods. What motivates us is the satisfaction of finding clever ways to manipulate information with molecules to do surprising and useful things! Potential projects could involve a combination of the following areas depending on your interests and background:

Computational & Dry-Lab:

• Mathematics & network science
• Bioinformatics
• Machine learning & optimization

Experimental & Wet-Lab:

• Surface/polymer chemistry/materials engineering
• Molecular biology/biochemistry
• High-throughput DNA sequencing
• Device construction & fluidics

Want to do a postdoc with us? The best way is to co-apply with us for external funding. Here is a list of options to consider:

• DDLS Postdoctoral Fellowship For computational projects. Deadline in March.
• Digital Futures Postdoc Fellowship (announced mid-February, decisions in June)
• RED Postdoctoral Fellowship (posted each year around December)
• Marie-Curie Fellowships (deadlines typically in September)
• EMBO fellowships