DC 13: Virtual screening and design of riboswitch ligands

PhD project description:

The PhD project will focus on using computational methods for hit discovery for the SAM-III, SAM-I/IV and FMN riboswitches. In particular, you will carry out structure-based virtual screening of ultra-large chemical libraries and chemical spaces containing millions to billions of compounds. Further, you will optimize the hits discovered by virtual screening and fragment screening (WP2) by designing analogues. The compounds will be either purchased or synthesised and tested for binding by fellow students.

Further, our collaborator Nicholas Pearce has developed software that allows analysing data resulting from crystallographic fragment screening (PanDDA). In collaboration with him, you will expand the PanDDA capabilities, so that also RNA crystals can be processed. You will subsequently apply this tool to analyse the crystallographic fragment screening data obtained in the TargetRNA network.

Research environment:

You will work in a team together with other PhD students and postdocs, both within the TargetRNA doctoral network, the research group, and at your secondments at CrystalsFirst and LiU. The work tasks will be varied, and you will learn a range of computational methods for hit discovery and optimization of RNA ligands and analysis of crystallographic fragment screening data.

The PhD position is associated to the Brenk  lab, which is part of the research unit for Structural biology and drug discovery

Skills/qualifications:

• Applicants must hold a master's degree or equivalent education in computational chemistry, cheminformatics, medical chemistry, pharmacy, or a related discipline. The master's degree has to be equivalent to a 5-years master's degree obtained in Norway. Master students can apply provided they complete their final master exam before 01.11.2024. It is a condition of employment that the master's degree has been awarded.

• Applicants must have a documented practical and theoretical background within cheminformatics or structure-based drug design.

• Applicants must have basic programming skills.

• Experience with Python and RDKit is an advantage.

• Experience with structure-based virtual screening is an advantage.

• The candidate must demonstrate a strong commitment and enthusiasm for the discovery of RNA-ligands and for research in the TargetRNA network in general.

• The candidate must be able to work independently and interactively in a team setting.

• A structured approach to work and excellent communication skills and fluency in both written and spoken English  are required

Personal and relational qualities will be emphasized. Ambitions and potential will also count when evaluating the candidates.

Organized research training (PhD program): The candidate must take part in the University of Bergen approved PhD programme leading to the degree within a time limit of 3 years. You must have admission to the organized research training (PhD program, see the reqirements here) at the Faculty in order to qualify for the position. Application for admission to the PhD programme, including a project plan outline for the training plan must be submitted no later than three months after the date of commencement.

The PhD-position: PhD-positions are fixed term positions. You cannot be employed in a PhD-position for more than one fixed term period at the same institution or have had similar employment at an institution in the region.

The University of Bergen is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications. The University of Bergen applies the principle of public access to information when recruiting staff for academic positions.

Benefits/salary/social security:

• Exciting development opportunities as part of your role in a strong professional environment.
• Salary at pay grade 55 (code 1017/pay framework 20.10) NOK 540 500 before taxes, in the state scales. Further increases in salary will be based on seniority in the position.
• Enrolment in the Norwegian Public Service Pension Fund.
• Good welfare benefits.

State employment shall reflect the diversity of Norwegian society to the greatest extent possible. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position.The University of Bergen applies the principle of public access to information when recruiting staff for academic positions. Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request is not met. Further information about our employment process can be found here.

For more information about the position, please contact Ruth Brenk.