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Postdoctoral Research Fellow position within Artificial intelligence enabled structure-based drug design at the Department of Biomedicine

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 European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101126560 and the University of Bergen.

The position is open to an incoming candidate, see LEAD AI mobility rules

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).

The advertised position will be attached to the eHACS project (Escaping the Combinatorial Explosion: Expert-Enhanced Heuristic Navigation of Chemical Space) which is about integrating knowledge-based expert guidance, modern molecular design, and empowering AI with the goal to develop a new De novo design method. More information about eHACS can be found here: https://www.uib.no/en/rg/brenk/152446/escaping-combinatorial-explosion-expert-enhanced-heuristic-navigation-chemical-space

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. In fact, the field is so attractive that new methods are almost published weekly. However, the validation of the AI methods is often very limited. Mostly, no activity data for AI-generated or -scored compounds is presented. If such data is included, it is typically limited to protein kinases which are considered to be easy targets due to wealth of published data.

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 the enzymes FabF and NMT for which we can routinely obtain binding data and high resolution crystal structures (Espeland LO, Georgiou C, Klein R, Bhukya H, Haug BE, Underhaug J, Mainkar PS, Brenk R.

An Experimental Toolbox for Structure-Based Hit Discovery for P. aeruginosa FabF, a Promising Target for Antibiotics. ChemMedChem. 2021., Kersten C, Fleischer E, Kehrein J, Borek C, Jaenicke E, Sotriffer C, Brenk R. How To Design Selective Ligands for Highly Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System. J Med Chem. 2020). The lessons learned from the validation shall also be used to develop improved methods.

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 a dedicated supervision and mentoring, encouraging inter-sectoral exposure, in particular:

academic freedom
benefits from knowledge and skills transfer between disciplines, organisations and sectors
structured, skill-based training
high-quality working conditions
personal career support
equal opportunities

For more information see the LEAD AI webpage or send an email to leadai@uib.no

Qualifications and personal qualities:

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 defence 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.
The LEAD AI mobility rules must be followed.
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.

Special requirements for the position
The University of Bergen is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications.

About the position of postdoctoral research fellow:

The position of postdoctoral research fellow is a fixed-term appointment with the primary objective of qualifying the appointee for work in top academic positions. You cannot be employed as a postdoctoral fellow for more than one fixed term period at the same institution.

The position may be extended by up to one year (maximum 4 years in total) if the appointee is granted externally financed research stays abroad.

Individuals may not be hired for more than one fixed-term period as a postdoctoral research fellow at the same institution.

For all LEAD AI fellows, a Personal Career Development Plan (PCDP) will be developed jointly by the fellow, supervisor, and co-supervisor by the end of Month 3 of the fellowship, including a plan for the individual research budget, and information on additional funding where applicable.

It is a requirement that the project is completed in the course of the period of employment.

We can offer:

An engaged and professionally stimulating working environment.
position as postdoctoral fellow (code 1352 in the basic collective agreement) and a gross annual salary of NOK 624 500 upon appointment. For applicants with a medical specialization, salary NOK 657 300. Further increases in salary are made according to length of service in the position. A higher salary may be considered for a particularly well-qualified applicant.
Welfare benefits* and social benefits including pension-saving in the Norwegian Public Service Pension Fund, occupational injury insurance, full salary during sick leave for 52 weeks, and paid parental leave**.
Extension of the position term (work contract) due to sick leave and parental leave.
Norwegian language courses free of charge.
High standards for working hours, holidays, place of work, health, and safety.
Access to specific training activities exclusively provided within the framework of the LEAD AI programme.

*) Subject to membership in the Norwegian National Insurance Scheme.

**) Right to paid parental leave requires 6 months paid work before first day of leave. See full requirements.

How to apply:

Before starting the online application process, please familiarise yourself carefully with our application requirements in the Guide for Applicants and Application templates It is essential that all required attachments (see next section) are uploaded via our electronic recruiting system JobbNorge. Before uploading any documents in the portal (to minimise repetition of information):

In the ‘JobbNorge-application field’: Only write your name.
In the ‘JobbNorge-CV form’: Only fill in your 1) personal details, 2) information about your PhD-degree (in the field ‘Academic qualifications’) and 3) recent relevant work experience.
You do not need to fill in any other sections in the JobbNorge form, as all the information we need will be provided by you when attaching the mandatory elements listed in the next section.

Your application must include:

Research proposal (5 pages, using a template based on the evaluation criteria), must be relevant to the AI-related research themes defined by LEAD AI host research groups in the call. It is essential that you discuss the details of the project idea with your potential UiB supervisor at an early stage in the application process, to ensure that there is a match between resources and expertise needed to implement the project.
A motivation letter.
A CV detailing the full scientific track record, relevant other achievements and career breaks (e.g., parental, and long-term sick leave, compulsory military service, and non-academic work)
Mobility declaration with supporting documentation (e.g., employment contract, rental agreement. etc.).
Table of potential ethics and security issues that might apply to the research proposal (self-assessment).
An initial self-assessment of opportunities for mandatory and recommended open science practices.
Scanned copy of the PhD diploma or documentation of formally delivered doctoral thesis (translated to English if necessary; Scandinavian languages are accepted).
References. Letters of recommendation from the graduating university or previous employers are encouraged.

The application and appendices with certified translations into English or a Scandinavian language must be uploaded at Jobbnorge

Evaluation

We anticipate the whole evaluation procedure to take approximately 4 months from application deadline. Eligible applicants will be evaluated by three internationally renowned experts and assessed against criteria addressing excellence, impact, implementation, quality of the researcher and training, and knowledge transfer. Details are stated in the Guide for applicants.

General information:

For further details about the position, please contact:

Prof. Dr. Ruth Brenk, Department of Biomedicine, ruth.brenk@uib.no, +47 55586070
For HR related questions contact: Selina Sia Hausberg, Medical Faculty, selina.hausberg@uib.no, +47 55585289

Diversity is a strength that enables us to solve our tasks even better. UiB therefore needs qualified employees regardless of gender, ethnicity, religion, worldview, disability, sexual orientation, gender identity, gender expression, and age.

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 to be omitted is not met.

We encourage applicants with disabilities, immigrant backgrounds, or gaps in their CV to apply. By indicating such circumstances in your application, you may receive favourable consideration. We ensure that at least one qualified applicant from each of these groups is invited for an interview as part of our commitment to inclusivity and equal opportunity.

Further information about our employment process can be found here.

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