Quick answer
The MSCA Excellence section should read as one integrated argument. The research objectives, methodology, supervision, training, two-way knowledge transfer and applicant profile need to explain why this project should be done by this researcher in this environment now.
For Postdoctoral Fellowships, Excellence carries the largest weighting in the evaluation framework. The exact subcriteria must always be checked in the current call documents.
Begin with the scientific problem
Start by making the problem legible.
A good opening normally establishes:
- what is known;
- what remains unresolved;
- why that unresolved point matters;
- what the project proposes to determine;
- what would be different if the project succeeds.
Avoid beginning with a long literature review. The evaluator needs the research logic before the literature density.
Objectives should resolve uncertainty
Objectives become stronger when they describe what will be learned rather than what will be done.
Compare:
Develop a new imaging platform.
with:
Determine whether the proposed imaging mechanism can resolve process X under conditions where current methods fail.
The first is an activity. The second is a scientific objective.
A small number of precise objectives makes it easier to connect methodology, training and impact.
State of the art should create the need for the project
A state-of-the-art section is not a catalogue of citations. It should establish the boundary the project is crossing.
A clean sequence is:
current capability -> limitation -> unresolved question -> proposed advance
The proposal should make clear what is genuinely new and why existing approaches cannot already answer the question.
Methodology must be rigorous without dominating the section
MSCA proposals need a sound methodology. More detail does not automatically produce more confidence.
The evaluator should understand:
- the core methods;
- why they answer the objectives;
- how methods interact;
- important assumptions;
- key risks and alternatives;
- relevant interdisciplinary dimensions;
- open-science practices;
- gender or other diversity dimensions where scientifically relevant.
Methodology should support the scientific argument. It should not turn the proposal into a methods paper.
Supervision should solve specific needs
Do not describe a supervisor mainly through prestige, publication count or title.
Explain why the supervisor is useful for this fellowship.
For example:
- expertise in a method the researcher needs to acquire;
- access to a scientific community the applicant does not yet have;
- experience leading interdisciplinary or intersectoral work;
- complementary knowledge required for the research question;
- mentoring experience relevant to the applicant's intended career transition.
The supervision plan should also explain frequency, structure and how scientific/career progress will be monitored.
Training should be derived from capability gaps
Start from the future researcher you are trying to create.
List the capabilities needed to reach that state, then design training around them.
Examples include:
- a specific experimental technique;
- advanced statistics or AI methods;
- scientific leadership;
- IP and technology transfer;
- project management;
- supervision experience;
- teaching;
- industry exposure;
- communication to specialist and non-specialist audiences.
Generic training catalogues weaken the sense that the fellowship has been designed around one researcher.
Two-way knowledge transfer should be reciprocal
A good proposal explains both directions.
Researcher -> host: what distinctive knowledge, methods or networks arrive with the applicant?
Host -> researcher: what expertise, infrastructure or practices will be acquired?
Interaction: what becomes possible because those capabilities meet inside the project?
That third line is often the most interesting.
The researcher's profile should show readiness, not perfection
The applicant does not need to look complete. A fellowship exists partly because there is development still to do.
The profile should show:
- enough expertise to execute the project;
- evidence of contribution and research maturity;
- a credible reason for the next training step;
- a direction that becomes stronger through the host environment.
The gap between current profile and future profile is part of the proposal logic.
Use one conceptual diagram if it saves text
A compact figure can help if it clarifies the project architecture, knowledge-transfer loop or research-to-training relationship.
For example:
research question -> objective 1/2/3 -> methods -> training needs -> new capability
The figure should replace explanation, not decorate it.
A review test for Excellence
Read the section once without looking at the work plan and ask:
- Can I state the central question in one sentence?
- Is the advance beyond the state of the art explicit?
- Do the methods directly test the objectives?
- Does the applicant need this host?
- Does the host need something the applicant brings?
- Is the training specific to the researcher's future direction?
- Does the section read as one design rather than six mandatory subsections?
If those answers are clear, the section is doing its job.
Related MSCA resources
- Postdoctoral Fellowship strategy guide
- MSCA Impact guide
- Supervision, training and knowledge transfer
- RADIANCE PF handbook practical review
Need an Excellence review?
Arvacore can review the scientific argument and the links between objectives, methodology, supervision, training and knowledge transfer without rewriting the proposal into generic grant language.