Postdoc in quantitative characterisation of multivalent binding Full-time NEW

Postdoc In Quantitative Characterisation Of Multivalent Binding

We are looking for a postdoc to develop new methods for measuring multivalent binding — the mechanism by which antibodies and many modern therapeutics engage several targets at once. Standard binding assays capture this poorly, which limits how well the behaviour of such molecules can be predicted.

The project combines DNA nanotechnology with amplification- and sequencing-based readouts. You will use programmable DNA nanostructures to present targets at controlled nanometre spacings, and develop assays that quantify how binders engage them. The work is method development with applications in mind, carried out together with the experimental and computational members of the group at the Department of Gene Technology, KTH/SciLifeLab.

Qualifications

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.
• Documented experience of quantitative molecular biology methods, such as qPCR, digital PCR or DNA sequencing.
• Very good command of English, spoken and written, as this is the working language of the research group.

As a person you are independent and used to driving a research project forward on your own initiative. The work takes place in an interdisciplinary environment, which calls for good collaborative skills and the ability to communicate results clearly. We prefer that you are aware of diversity and equal opportunity issues, with specific focus on gender equality.

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline.
• Experience of DNA nanotechnology or other forms of programmable molecular self-assembly.
• Experience of characterising molecular binding interactions, for example using surface-based or biophysical methods.
• Ability to combine experimental work with quantitative data analysis or modelling.
• Experience of supervising students or teaching at university level.

Great emphasis will be placed on personal skills.

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