Methodology Scientist

InstitutionALBA is the Spanish synchrotron light source, a large research infrastructure operating ten beamlines, complementary facilities, and an Electron Microscopy Center, this last in partnership with other institutions. Currently constructing multiple more beamlines, expanding the Electron Microscopy Center, and integrating advanced data analytics, it sums up a wide range of infrastructures geared toward finding solutions to societal challenges.
InstitutionALBA is the Spanish synchrotron light source, a large research infrastructure operating ten beamlines, complementary facilities, and an Electron Microscopy Center, this last in partnership with other institutions. Currently constructing multiple more beamlines, expanding the Electron Microscopy Center, and integrating advanced data analytics, it sums up a wide range of infrastructures geared toward finding solutions to societal challenges. Located in Cerdanyola del Vallès (Barcelona, Catalonia, Spain), it is funded by the Spanish Government (Ministerio de Ciencia e Innovación) and the Catalan Government (Generalitat de Catalunya, Departament de Recerca i Universitats). The synchrotron light produced by 3 GeV electrons is used by thousands of researchers to analyse and understand the properties and functionality of matter, spanning a wide variety of fields, such as catalytic research, health, energy production/storage, environmental research, communication technologies, or cultural heritage. Our highly motivated staff works in a multidisciplinary work environment with an atmosphere formed by lived diversity, inclusion and respect for our colleagues. One of the goals of our gender equality plan is to reach parity within the Consortium’s different divisions and offices, and several actions have been taken to encourage applications from women mostly in scientific, engineer and technical job positions. Located close to Barcelona in a natural park and well connected by car and public transportation, with excellent connectivity to the world and an employer who understands the importance of life-work balance. Facing an upgrade to ALBA II, a 4th generation facility, which will increase dramatically brightness and coherent flux, ALBA is in a phase of growth and dynamics. Being a part of the ALBA team will promote your career and will give you the opportunities to explore new territories. For more information, you can take a look on our history watching this video: https://www.
Youtube.
Com/watch?v=gHMqiH4qBAoTasksThe Methodology Group at ALBA develops scientific methodologies, algorithms and software needed to process and analyse large and heterogeneous datasets to support academic and industrial users to tackle complex scientific problems. By participating in pilot projects in key research areas for both academia and industry, the Methodology group combines data analysis of different provenance, including community or consortium-owned databases, and integrating theoretical and simulation-based data. A growing part of this activity consists of adapting technique-specific analysis pipelines and methodologies into robust, reusable and automated data analysis workflows that can be deployed on local, high-performance and cloud computing resources and reused across beamlines, techniques and scientific cases.
Specifically, The Responsibilities Will Include
- Designing and developing end-to-end data analysis pipelines — from raw data ingestion, reduction and pre-processing to analysis, visualisation and reporting — for data produced at synchrotron radiation beamlines and at electron microscopy facilities.
- Developing data analysis workflows within pilot projects that serve as a testbench to build and validate these methodologies before adapting them for broad usage. For example, combining X-ray diffraction with complementary X-ray absorption spectroscopy, computed tomography and 4D-STEM datasets, including pre-processing steps that optimise computational performance and data-driven or machine-learning-based methods.
- Adapting existing technique-specific analysis tools and prototypes into modular, configurable and well-documented software components that can be reused across techniques, instruments and scientific cases, and packaging them for distribution.
- Automating analysis workflows and their orchestration, including scheduling, parallelisation, monitoring, error handling, provenance tracking and quality control, so that analysis can run unattended during and after experimental campaigns and, where relevant, in near real time.
- Deploying and optimising these workflows on the available computing infrastructures (local servers, computing clusters and cloud services), collaborating with the Computing Division to define containerisation, resource management, data access, storage and API strategies, and to ensure stable and maintainable services for users.
- In collaboration with the Scientific Data Management section and external partners, structuring and curating the assoc