Methodology Scientist

Tasks

The 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.

The selected person will report to the Head of the Methodology Group and will be responsible for the design, development and deployment of data analysis pipelines for multimodal experimental data, with a strong emphasis on automation, reusability and reproducibility. The position implies working in close synergy with beamline scientists, the Joint Electron Microscopy Center at ALBA (JEMCA), other members of the Experiments Division, the Computing Division, in particular the Scientific Data Management Section, and the Industrial Office, as well as external partners.

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 associated (meta)data — data models, formats, catalogues and interfaces — in line with FAIR principles and with ALBA’s scientific data management policy, so that results are traceable, reproducible and reusable.

• Documenting the developed tools, preparing user guides and training material, and providing scientific and technical support to their users.

• Providing Local Contact services to users of workflows as required.

• Contributing to the scientific and technical activity of the group: participating in data acquisition campaigns when appropriate, taking part in ongoing national and European projects and collaborations, and disseminating results through publications, open-source software releases, presentations, project deliverables and reports.

• Communicating with the potential or existing user community for identifying needs and optimally tune the services for high impact.
• Any other task or duty of a similar nature, consistent with the job category and with the responsibilities, professional level, and functional scope of the position, that may reasonably be assigned by Management whenever necessary to ensure its proper functioning.

Requirements

The requirements for participation must be met on the date of the deadline for the submission of applications and will be accredited by means of the CV attached to it, without prejudice to the power of the selection body to require the contribution of the originals of the certifications accrediting the qualifications, training and work experience invoked in the CV.

Applications that do not present the aforementioned or required documentation during the selection procedure will not be accepted.

The successful candidate must:

• Master’s degree in Computer Science, Software Engineering, Data Science, Physics, Engineering, Mathematics, Chemistry, Materials Science or a related field. Foreign qualifications will be assessed following the classification of academic fields of Annex II of Royal Decree 967/2014, of 21 November.

• At least 2 years of demonstrable professional or research experience in data analysis and/or scientific software development, including programming in Python (or an equivalent language) applied to data processing. Experience acquired in industry, in academic research (including postdoctoral work) or in research infrastructures will be valued on equal terms.

Everyone who meets the requirements will be admitted for the selective process. This position is reserved for those candidates having the legal status of person with disabilities, with a degree of disability equal or greater than 33%. In case of one or more admitted applicants with this status of disability, these candidates will be evaluated at first. In the event that no candidate with the status of disability is finally selected for the position, the selection process shall continue and the rest of the applicants will be evaluated.