About
I am a scientific data analyst with a PhD in astrophysics and 8+ years of experience across research and industry, based in the Heidelberg area.
I have worked on Python-based scientific computing, data integration, validation and quality control.
I am strengthening my supervised learning skills in Python, with a focus on training and evaluating models and real-world applications.
I am now looking to apply this experience in a technical data or software role.
Analytical methods
Time-series analysis · Supervised learning · Statistical modelling · Data visualisation · Data validation
Tools & libraries
Python · NumPy · pandas · SciPy · Astropy · scikit-learn · Flask · SQL · Git
Positions
Career history, education, research questions and collaborations.
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2024–2026
Postdoctoral Researcher · Scientific Data Analyst
Centro de Astrobiología (CAB), based at ESAC
Developed Python workflows for stellar spectroscopy and investigated calibration anomalies in high-precision measurements.
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2024
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2018–2023
PhD in Astrophysics
CAB; visiting researcher at MPIA, Heidelberg
Built Python pipelines to integrate and validate catalogue data for studies of M-dwarf properties and multiplicity.
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2017
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2017
MSc in Astrophysics
Universidad Complutense de Madrid (UCM)
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2014–2016
Technical Consultant · Smart Energy
Indra Sistemas (Minsait), Madrid
Coordinated device requirements with suppliers and software teams, worked with clients, and prepared energy-monitoring reports.
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2014
Research Trainee
CIEMAT
Conducted experimental measurements and analysed materials for solar energy.
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2014
MSc in Renewable Energies
Universidad Autónoma de Madrid (UAM)
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2013
Degree in Physics
Universidad de Salamanca (USAL)
Question A
Triple Trouble: Exoplanets in hierarchical triple systems
Triple star systems are more common than often assumed, yet planets in them remain understudied. Their orbital architectures offer valuable clues about planet and star formation in complex gravitational settings.
Exoplanets
Binaries
Dynamics
Question B
One is the Loneliest Number: Triple stars are everywhere
Gaia astrometry reveals subtle anomalies in stars that appear single, hinting at unresolved companions. This project follows up such cases to identify spectroscopic binaries.
Binaries
Spectroscopy
Gaia
PI: J. Lillo Box
The KOBE experiment is a legacy radial-velocity survey using CARMENES at Calar Alto. By targeting the overlooked K dwarfs, KOBE bridges the gap between G- and M‑dwarf studies.
Team member
PIs: P.J. Amado, A. Quirrenbach
CARMENES is a dual-channel high-resolution spectrograph operating at the 3.5m Calar Alto telescope, dedicated to the detection of terrestrial-mass exoplanets around M dwarfs.
Consortium member
CARMENES @ Calar Alto 3.5m
High-resolution visible and near-infrared spectroscopy for radial velocity measurements and stellar characterization
PI on proposals
Co-I on proposals
Observing runs
Regular observing campaigns for stellar multiplicity and exoplanet detection programs
- Triple star systems with planets
- Spectroscopic binaries in KOBE sample
- Young M dwarf characterization
Projects
Code, methods and results from projects built around stellar data.
RUNA
Machine learning
Python
scikit-learn
pandas
NumPy
Matplotlib
RUNA is a command-line machine-learning application: enter two brightness measurements (G and J) to estimate a cool star's spectral subtype. The project compares a simple regression model with a random forest on held-out stars; the current two-input prediction uses the simpler model.
KOBE stellar characterisation
Data pipelines & quality control
Python
Astropy
NumPy
SciPy
Matplotlib
Turns telescope spectra into estimates of a star's temperature and chemical composition. The Python workflow prepares the measurements, flags results that need review, and checks them against well-studied reference stars. Telescope data must be supplied separately.
Multiplicity in cool dwarfs
Data integration & validation
Python
NumPy
SciPy
Astropy
Matplotlib
pyperclip
Cross-checks astronomical data to identify stars with companions, then produces a table and figures for 22 systems. The publication reports 11 newly identified systems. The workflow demonstrates how to combine, validate and communicate results from multiple data sources.
Queries
Two simple searches: one for my thesis text and one for selected public VizieR catalogues. The thesis search uses a separate service.
Publications
These publications provide the scientific foundation for the code projects featured here. All my publications are listed on ADS. For more details about my scientific output, see my CV.
Keywords: cool stars · binaries · exoplanets · radial velocity
First-author publications
2025
Cifuentes et al.
Complete multiplicity study ranging from close spectroscopic binaries to ultra-wide companions.
2021
Cifuentes et al.
Gaia EDR3 study of known and newly identified multiple systems containing cool dwarfs.
2020
Cifuentes et al.
Benchmark study of colours and stellar parameters in the CARMENES input catalogue.
Co-authored articles
2026
Lillo-Box et al.
Follow-up of TESS candidates with radial velocities and photometry.
2025
Balsalobre-Ruza et al.
Two super-Earth- or sub-Neptune-mass planets orbiting a quiet K7 star.
2024
Cortés-Contreras et al.
Kinematic analysis of 2187 M dwarfs, identifying 191 young star candidates.
2024
González-Payo et al.
Study of 212 exoplanet host stars in multiple systems.
2022
Caballero et al.
Characterisation of the nearby warm rocky planet Gl 486 b.
2021
Marfil et al.
Spectral-synthesis study of stellar parameters for 343 M dwarfs.
2019
Martínez-Rodríguez et al.
Analysis of the potential for stable exomoons around M-dwarf planets.
2019
Schweitzer et al.
Comparison of methods for radii and masses of nearby M dwarfs.
Thesis
2023
C. Cifuentes · PhD thesis