S-NGLE TECHNOLOGIES

Target group

The project is available for PhD students (1 month) or for postdocs and researchers (up to 3 months), depending on experience and fit.

About the company

Single Technologies is a Stockholm-based deep tech company aiming to transform the data generation in sequencing completely through our patented 3-D Sequencing™, a truly disruptive technology.

Single Technologies was founded in 2014 as a unique combination of research from the Royal Institute of Technology and R&D in the fiber optical grating industry. A strong multidisciplinary team is pushing the limits of what the industry assumes is possible when it comes to sequencing and Big Data generation.

The project

This internship offers a unique opportunity for a PhD student or postdoctoral researcher with strong expertise in in situ gene expression profiling to contribute to the development and validation of our in situ sequencing (ISS) platform. The work will involve optimizing tissue and cell preparation, signal generation, sequencing and imaging workflows; troubleshooting technical issues; and potentially benchmarking assay performance against orthogonal methods.

The internship is laboratory-focused and will provide the candidate with the opportunity to apply their expertise in assay development, hands-on troubleshooting, and protocol validation. The expected outcomes include optimized workflows, reproducible protocols, validation datasets, and recommendations for further development.

The internship will be performed at Single Technologies’ premise at Sankt Eriksgatan 48F, Stockholm. The internship’s timing and format are flexible and will be arranged together with the candidate.

The candidate

We seek a PhD student or postdoctoral researcher with intensive experience in in situ gene expression profiling (e.g., ISS, MERFISH, seqFISH, or related techniques). Essential skills include tissue and cell handling, hybridization/ligation-based chemistries, fluorescence microscopy, and assay troubleshooting. Experience with orthogonal validation methods is strongly preferred. Familiarity with computational analysis pipelines is welcome but not required.

Contact information

Name: Xiang Jiao

Email: xiang@singletechnologies.com

Company website: https://www.singletechnologies.com/