Descripción de la oferta
ALBA 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:
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.
Selection Process Development
The selection will be carried out through the competition-opposition system.
As a first phase, an analysis of the curriculum will be carried out (assessment of previous experience and / or scientific history, degree, training and other professional information relevant to the position). Career breaks or variations in the chronological order of CVs will be regarded as an evolution of a career, and consequently, as a contribution to the professional development.
The assessment of the CV in the competition phase will be scored up to 40 points, which will consider the following aspects:
Criterion
Points
Doctorate in one of the fields listed in the requirements
5
Experience in the development of data analysis pipelines and/or scientific software
up to 9
More than 4 and up to 6 years
3
More than 6 and up to 8 years
6
More than 8 years
9
Experience and training in AI and machine-learning methods
up to 5
Application of AI/ML methods to data analysis (e.g. PCA/decomposition, classification, regression ...), including the development or training of models integrated into analysis pipelines
up to 3
Integration of AI agents or LLM-based components into workflow orchestration and automation
up to 2
Experience and training in automation, reusability and software engineering practice
up to 8
Automation and orchestration of data workflows (e.g. Airflow, Snakemake, Nextflow, or equivalent)
up to 4
Software engineering good practices: version control, testing, CI/CD, containerisation, packaging and documentation
up to 4
Experience and training in cloud and distributed computing
up to 7
Hands‑on deployment of data workflows on cloud services and/or HPC or cluster environments
up to 5
Accredited cloud certifications (AWS, Google Cloud, Azure) or equivalent specialised training
2
Experience with X‑ray and/or electron technique data (spectroscopy, diffraction, imaging/tomography)
up to 6
Data analysis experience with one of these techniques
3
Data analysis experience with two or more techniques and/or correlative multimodal analysis
6
The best rated candidates, at least two if possible, will be invited to an interview where the technical competence, knowledge, skills and professional experience linked to the position will be assessed, with a total score of 60 points. A minimum of 30 points must be obtained out of a total of 60 points to be eligible.
Provided they meet the minimum requirements and have ranked among the top five after the assessment of the CV phase, at least one person from the underrepresented gender in the division/office will be interviewed.
The interview will include at least:
Presentation of professional experience: 10 pointsTechnical knowledge and problem‑solving related to the position (programming, data analysis pipelines, automation, cloud computing, scientific data analysis ...): 20 pointsAuto‑assessment of soft skills, teamwork and ability yo interact with others: 10 pointsVision of the job position: 10 pointsMotivation for applying: 5 pointsCommunication skills in English within a multidisciplinary and international environment: 5 points
The merits will be accredited by means of the CV attached to the application. The selection board may require accreditation by additional documentation, originals or certified copies confirming the experience invoked in the CV.
In case of a tied final score, the position will be awarded to the person who belongs to the most underrepresented gender in the corresponding Division and subsidiarily to the overall company.
If necessary, alternates of the members of the selection board will be appointed by the president of the selection process, and the change will be published in the announcement.
The resolution of the selection procedure will be carried out within a maximum period of six months from the deadline for submitting applications for participation.
The selection process may be declared vacant if the selection board considers not to have found eligible candidates for the position although they might meet the requirements to participate in the selection process specified in the offer.
Other information
Base salary range €41.063 – €46.798 gross per year.
The base salary offered will be determined according to the selected candidate's qualifications, relevant professional experience, competencies and overall suitability for the position.
Additional remuneration: annual productivity bonus (approximately 4% of the base salary), subject to the applicable internal policy and performance evaluation.
ALBA also offers an attractive employment conditions, including flexible working arrangements and professional development opportunities.
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