Ideas

Electronic Lab course. Heard of this in Erlangen for physics. Talks about ELN among other things.

Original Motivation

The target audience for such a master’s programme would be students holding a bachelor’s degree from a domain science, which we will call home domain in the following.

There is explicitly no restriction on the candidates’ home domain: it may be from the STEM disciplines, life sciences, humanities or social sciences. Candidates with a bachelor’s degree in computer science are also explicitly included, although we acknowledge that their master’s programme should include adaptations to make their interaction effective with other domain scientists.

In order to give the future RSE the necessary breadth, we expect this to be a four semester curriculum.

The curriculum is formed from a combination of modules, some of which are core modules teaching essential skills that must be completed by all students. Other modules introduce more specialised concepts and skills.

During the master’s programme, students should pick an RSE specialisation from the list in this paper and attend these additional modules to deepen their knowledge in the field.

Core modules are of course drawn from the three pillars of the RSE and can be categorised accordingly.

Software / Technical Skills

Foundational module
Introduction to programming: Emphasising use cases over programming paradigms, students learn at least two languages:
- A language that facilitates prototyping and data processing e.g., Python or R
- A language for designing complex, performance-critical systems e.g., C/Cpp
  This exposes them to computers in a hands-on fashion and is the foundation for DOCBB, DIST.
Computing environment module
Programming languages are not enough to work in a landscape of many interconnected software components. Hence, we require something like software craftsmanship:
- Tools: Unix shell, version control systems, build systems, documentation generators, package distribution platforms, and software discovery systems
  This strengthens skills in DIST, DOCBB, SWREPOS, SRU.
Software engineering module
Develop foundational software engineering competencies:
- Requirements engineering
- Software architecture and design
- Implementation, quality assurance, and software evolution
  Emphasising and strengthening DOCBB, DIST on a more abstract level.

Research Skills

Optional domain mastery module
Additional minor research courses; students with a home-domain already have the research part well-covered.
Research tools module
Teach tools used to distribute and publish software, and introduce domain-specific data repositories, gaining foundational knowledge in SRU, SP, DOMREP.
Meta-research module
Teach how research works: Introduce the research life cycle, the data life cycle, and the software life cycle abstractly.

Communication Skills

Project management methods
Teach project management methods that are useful in science, such as agile ones PM.
Communication skills module
Courses focusing on:
- Interdisciplinary communication
- Interacting across cultures
- Communication in hierarchies
- Supporting end users effectively
  All facets of the USERS skill.
Teaching module
Covers topics to effectively design courses and teaching material for various digital tools, strengthening the TEACH skill.

Hands-On Practice

RSE work also involves craftsmanship skills. Hands-on practice is integral.

At least two lab projects are required within the mandatory curriculum.
These should be team-based and involve a question from a domain science.
Ideally, projects cover both the candidate’s home domain and another domain.
Projects should stem from collaborations with scientists within the institution, with RSE students taking on a consultant role.

This setup strengthens TEAM, TEACH, USERS and likely also MOD through interaction.

To emphasise exposure beyond their bachelor’s domain, RSEs should support their non-home-domain project with introductory courses from that discipline. This encourages adapting vocabulary and thinking—an aspect of MOD.

Optional Modules and Specialisations

To align with the specialisations listed in this paper, example optional modules include:

HPC engineering / parallel programming
Numerical mathematics / scientific computing
Web technologies
Data stewardship
AI models / statistics
Community management / training

Master’s Thesis

The programme concludes with a master’s thesis that should:

Be dual-supervised by an RSE project supervisor and a domain supervisor
Answer a relevant research question strengthening NEW using computational methods
Include software development as a required, gradable deliverable

The RSE supervisor ensures and grades the software craftsmanship. This ensures the effective application of RSE skills in an actual research environment.