❗️ Scroll to the bottom of the page to find the application form 

Project Description

There are no accurate models for how trimeric autotransporters (TAAs) bind host effectors; all of the studies so far have involved mutagenesis and foot-printing. We aim to rectify this gap. AlphaFold does a poor job of modelling these structures and complexes (1) because they have unusual sequences and (2) because they aren’t globular.

The project involves studying TAAs from ESKAPE pathogens (eg Acinetobacter) to determine how they bind host effectors (collagen, laminin etc) via cryoEM and structural EPR spectroscopy (with Christos Pliotas, University of Manchester). The student will then connect this information to strain and variant differences/changes in virulence, as this will lead to improvements in diagnostics. We will the extend this work to model how invasins, related proteins, from at least one ESKAPE pathogen studied in StraDiVarious (K. pneumoniae and E. cloacae) bind their targets. 

Finally, we will model how the inside-out barrels insert into the membrane by studying the (BAM-invasin complex), building on work by our collaborator (Dirk Linke, University of Oslo). The project will allow both academic and industry secondments, using state of the art structural biology equipment.

Methods will include protein expression and purification of membrane proteins, as well as EPR spectroscopy (in Manchester) and cryoEM, both locally and on secondment. Modelling the complex with the latest tools and the validation of those models through mutagenesis will also be a key part of the techniques used.

Mandatory requirements

The candidate must have:

• Master’s degree or equivalent in Structural Biology, Molecular Biology, Biophysics, Biochemistry or related fields at the time of admittance to the programme

• Documented experience in at least one of the following areas: protein biochemistry, computational modelling, electron microscopy

Desirable qualifications

In addition, it is an advantage if the candidate has:

• A good theoretical understanding of magnetic resonance or structural biology

• Documented experience with protein expression and purification

• Documented experience in cryo-EM

Personal skills:

We are an international team of researchers from different scientific and cultural backgrounds. Therefore, the ideal PhD candidate should have:

• Good language and communication skills

• The ability to work in interdisciplinary teams

• The ability to work independently on complex projects (from planning and execution to results presentation)

In addition to the eligibility criteria (see below in "How to Apply"), candidates admitted to a PhD programme at the University of Helsinki must fulfil these requirements: https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes/eligilibity-doctoral-programmes

Supervisor Adrian Goldman (www.goldman-lab.org)

Hosting institution Helsinki University (Finland) (https://www.helsinki.fi/en)

Technical information:

• Position location: Helsinki, Finland.

• Application deadline: January 6th, 2026

• Interviews: February 9th and 13th, 2026 (be available both days)

• Project start date: September 1st, 2026

• Duration: 3 years

How to Apply

Find the eligibility and application requirements below.

Eligibility Criteria

• Applicants must not have been awarded a doctorate previously.
• Applicants must not have resided or carried out their main activity in the country of the recruiting institution for more than 12 months in the 3 years immediately prior to the date of recruitment. See: https://marie-sklodowska-curie-actions.ec.europa.eu/actions/doctoral-networks ‘What does the funding cover’
• Candidates must have a high level of English proficiency (demonstrated eg by TOEFL, IELTS certification) or by having been educated in an English-speaking country to age 18.
• Candidates must meet all eligibility criteria as outlined in the individual research project descriptions.
• Candidates must meet the entry requirements of the institution to which they apply.

Application Requirements
The candidates will be selected based on the quality of the application, expertise, work experience, and qualifications. In the first instance, an expression of interest should be lodged containing the following documents (in English) consolidated into one single PDF file. As mentioned above, it will increase your chances if you apply to more than one project.

• A current cv (resumé) (max 2 pages).
• A short cover letter, no more than 600 words, that covers the following:
  1: your motivation and key research experience/achievements that demonstrate independent thinking and your ability to complete a PhD. Evidence the skills you claim with the documents you give us.
  2: the original working title of your MSc or BSc thesis.
  3: The first scientific memory that you have (max 250 words)
• A clear statement if and how and what AI tools you used. We recommend you do not use them.
• The table of contents of your thesis
• A research outline (max 500 words) related to the DC topic in which you suggest how you can meet and develop further the research project described in the project advertisement. Be specific: where in your attached certificates can we find proof of the necessary qualifications for the given position?

The following items will be submitted in separately in the application form.

• We suggest you apply for up to 3 PhD positions in StraDiVarious. If you do, list two other choices in order of preference. (You do not need to provide further information.)
• Details of 2 referees (names, contact details) who can provide additional information about your qualifications.
• Official Academic Record - Bachelor's and Master’s Certificates and Transcripts.
• We expect that, since a Master’s Degree is required, you will either have completed it at the time of application, or will do so with the requisite grades and be able to provide a degree certificate by July 1st, 2026. In such a case, acceptance is conditional.
• Demonstration of English-language proficiency (official certificates from language tests, or based on your schooling and where you grew up).
• If we suspect unreported use of AI-generated text, we reserve the right to check using AI-text detection tools and summarily reject the application. This is consistent with our no-tolerance policy towards plagiarism.