Institution

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:

https://www.youtube.com/watch?v=gHMqiH4qBAo

Tasks The Methodology Group at ALBA develops the scientific methodologies, algorithms and software needed to process and analyse large and heterogeneous datasets, supporting academic and industrial users in tackling complex scientific problems. This postdoctoral position is dedicated to the scientific data analysis activities of the IMAGiC project, with a strong focus on extracting materials-science insight from multimodal X-ray and electron datasets.

The position is framed within the project Innovación en fabricación aditiva de metales para afrontar los nuevos retos del GigaCasting (IMAGiC), ref. CPP2024-011400, funded by MICIU/AEI. The project investigates additive manufacturing of metals for GigaCasting applications; ALBA leads the in-situ high-energy X-ray diffraction analysis and the development of data analysis tools for the resulting datasets, in collaboration with the other entities in the project consortium (ROVALMA, CENIM-CSIC and EURECAT).

The selected person will report to the Head of the Methodology Group and will work in close synergy with beamline scientists, the Joint Electron Microscopy Center at ALBA (JEMCA), the Computing Division, the Industrial Office, with the project partners and with external partners as required. The role emphasis is on the development and implementation of a data analysis workflow optimal for the physical and materials-science interpretation of the data, supported by modern data-analysis, AI/ML and software methods.

Specifically, The Responsibilities Will Include

- Analysing and interpreting multimodal experimental data from the IMAGiC campaigns, combining in-situ high-energy X-ray diffraction with complementary X-ray absorption spectroscopy, computed tomography and 4D-STEM, to characterise phases, microstructure, chemical composition and their evolution under processing conditions.
- Developing and applying data-analysis methods and scientific software (in Python or equivalent) for the reduction,



processing and quantitative analysis of these datasets, including data-driven and machine-learning approaches (e.g. decomposition, classification, regression) to detect and quantify subtle structural and chemical changes.
- Contributing to the design and validation of reusable, reproducible analysis pipelines for the project data utilizing ALBA's and its partners resources and following FAIR principles.
- Correlating the experimental results with the manufacturing and processing parameters of the study, and with theoretical or simulation-based data where relevant, to support the scientific objectives of the project.
- Disseminating results through peer-reviewed publications, conference contributions, open-source software releases, project deliverables and reports, and contributing to the scientific activity of the Methodology Group.
- Participating in data-acquisition campaigns at ALBA and, if appropriate, at other facilities, and providing scientific support to project collaborators and users.
- Collaborating with the main stakeholders involved — project partners, beamline and external scientists, and personnel from other institutions — and contributing, where relevant, to the deployment of the analysis workflows on external high-performance computing resources, like Barcelona Supercomputing Center (BSC).
- 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 hold a doctorate (PhD) in Physics, Materials Science, Engineering, Chemistry, 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.

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





- Scientific record and research experience (peer-reviewed publications, conference contributions and doctoral/postdoctoral research relevant to materials science, physics, chemistry or a related field) (Up to 8 points)
- Experience in the analysis of data from X-ray and/or electron techniques (spectroscopy, diffraction, imaging/tomography):
- Data analysis experience with one of these techniques (Up to 4 points)
- Data analysis experience with two or more techniques and/or correlative multimodal analysis (Up to 4 points)

- Experience in scientific software development and programming (Python or an equivalent language) applied to scientific data analysis (Up to 8 points)
- Experience and/or training in AI and machine-learning methods applied to scientific data analysis:

- Application of AI/ML methods (e.g. PCA/decomposition, classification, regression) (Up to 4 points)
- Building and training predictive or inference models (e.g. surrogate models, property prediction, forward/inverse modelling) as components of scientific analysis tools (Up to 2 points)

- Experience and/or training in Data analysis pipelines development, workflow automation and reproducible / FAIR data practices (Up to 6 points)
- Experience at synchrotron or other large-scale research infrastructures, and with in-situ / operando or multimodal experimental campaigns (Up to 4 points)

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

- Scientific and technical knowledge related to the position (interpretation of X-ray/electron data, data-analysis and AI/ML methods, materials-science understanding): 20 points
- Presentation of professional and research experience: 10 points
- Vision of the job position and its scientific objectives: 10 points
- Self-assessment of soft skills, teamwork and ability to interact with scientific users and partners: 10 points
- Communication skills in English: 5 points
- Motivation for applying: 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

Temporary contract.

Base salary range €37,708 – €42,983 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.

ALBA also offers an attractive employment conditions, including adaptable working arrangements and professional development opportunities.

The Selection Board is composed by the following members: Lucia Aballe Aramburu, Carlo Marini, Bárbara Machado Calisto and Joaquín Otón Pérez

📌 IMAGiC Data Analysis Workflows Scientist (Sardañola del Vallés)
🏢 ALBA Synchrotron
📍 Sardañola del Vallés