MSCA Cofund Postdoctoral Research Fellow within artificial intelligence

4 days ago

Bergen, Vestland, Norway University of Bergen Full time

Organisation/Company: University of Bergen

Department: Department of Biomedicine

Research Field: Chemistry » Biochemistry, Chemistry » Computational chemistry, Chemistry » Molecular chemistry, Chemistry » Structural chemistry, Computer science » 3D modelling

Researcher Profile: Recognised Researcher (R2)

Positions: Postdoc Positions

Country: Norway

Application Deadline: 11 May 2025 - 23:59 (Europe/Oslo)

Type of Contract: Temporary

Job Status: Full-time

Is the job funded through the EU Research Framework Programme? Horizon Europe – COFUND Marie Curie Grant Agreement Number 101126560

Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Postdoctoral Research Fellow position within Artificial intelligence enabled structure-based drug design

At the Department of Biomedicine (https://www.uib.no/en/biomedisin) in the group of Prof. Dr. Ruth Brenk (https://www.uib.no/en/rg/brenk), there is a vacancy for a postdoctoral research fellow position within Artificial intelligence enabled structure-based drug design. The position is for a fixed term of three years and is associated with the LEAD AI project co-funded by the European Union's Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101126560 and the University of Bergen (https://www.uib.no/en/leadai).

About the host research group and research theme:

The overall research goal of the Brenk lab is to improve methods used for structure-based drug design and to apply these methods to design inhibitors for enzymes with biological relevance. A key point in our research is the interplay of theoretical and experimental methods. More information can be found on our homepage https://www.uib.no/en/rg/brenk/98283/research-brenk-lab.

Currently, large research efforts are ongoing to develop AI methods suitable for De novo design, scoring functions to predict the affinities of the designed compounds, and docking methods. However, the validation of the AI methods is often very limited. The lack of validation using real-life drug discovery examples is seriously hampering the uptake of the methods in the field. Therefore, in this project we will work on validation of AI-based De novo design, scoring and docking methods using both retrospective and prospective predictions.

For the latter, we will make use of well studied systems in the Brenk group such as the enzymes FabF and NMT for which we can routinely obtain binding data and high resolution crystal structures.

Please note that the applicants need to submit a research proposal. In the selection process, the assessment of the research proposal will be an important criteria. It is therefore important that interested candidates contact the supervisor (Prof. Dr. Ruth Brenk, ruth.brenk@uib.no) as soon as possible to discuss a potential project.

About the LEAD AI fellowship programme:

LEAD AI is the University of Bergen's career and mobility fellowship program for training 19 postdoctoral fellows in artificial intelligence. The program has received funding from the European Union's Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101126560.

The LEAD AI program offers high-quality inter- and transdisciplinary research and training opportunities in the area of artificial intelligence supported by dedicated supervision and mentoring.

  • Academic freedom
  • Benefits from knowledge and skills transfer between disciplines, organisations and sectors
  • Applicants must hold a Norwegian PhD or an equivalent degree within medicinal chemistry or computational chemistry with a specialization in cheminformatics, structure-based drug design or a related field. PhD-students may apply if defense of the PhD-thesis is completed by 1.11.2025. It is a condition of employment that the PhD has been awarded.
  • Applicant should have a genuine interest in AI, and the research proposal must be related to artificial intelligence.
  • Applicants cannot previously have been employed as a postdoctoral fellow at UiB and they cannot be employed by any other institution for the time of the fellowship.
  • Research experience in ligand- or structure-based drug design is required.
  • Basic knowledge of a scripting language is required.
  • Experience with RDKit is a distinct advantage.
  • Experience with AI-related research and/or innovation is an advantage.
  • Experience with protein expression, binding assays and X-ray crystallography is an advantage.
  • Applicants must be able to work independently and in a structured manner and have the ability to cooperate with others.
  • Applicants must have excellent skills in oral and written English (self-assessed in the CV and demonstrated in the application).
  • The application and relevant documents must be in English.

Personal and relational qualities will be emphasized. Research experience, ambitions and potential will also be considered during candidate evaluation.

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