CV
General Information
| Name | Hilda Sandström |
| Position | Marie Skłodowska-Curie postdoctoral researcher |
| Institution | Technical University of Munich, Germany |
| hilda.sandstroem@tum.de | |
| ORCID | 0000-0001-7845-1088 |
| Google Scholar | scholar.google.com |
Core Competences
Scientific leadership · Project management · Molecular modelling & simulation · Structure prediction · Cheminformatics · Machine learning for chemistry · High-performance computing (HPC) · Student supervision & mentoring · Interdisciplinary collaboration · Scientific communication
Experience
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Since 10/2025Marie Skłodowska-Curie postdoctoral researcherTechnical University of Munich, GermanyMain project: Machine learning–based compound identification with mass spectrometry
- Developed machine learning models for mass spectrometry signal prediction and dataset similarity analysis.
- Develop protocols for simulating mass spectrometry data for atmospheric compounds.
- Coordinated interdisciplinary projects and supervised students.
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9/2024 – 9/2025Visiting postdoctoral researcherUniversity of Gothenburg, SwedenSimulated mass spectrometry signals using machine learning models, molecular dynamics, reaction exploration and quantum chemistry.
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9/2022 – 9/2025Postdoctoral researcherAalto University, FinlandMain project: Machine learning–based compound identification with mass spectrometry
- Developed machine learning models for mass spectrometry signal prediction and dataset similarity analysis.
- Designed molecular descriptors enabling interpretable machine learning models.
- Benchmarked models and descriptors for reaction rate prediction.
- Coordinated interdisciplinary projects and supervised students.
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9/2017 – 5/2022Early-stage researcher (PhD)Chalmers University of Technology, SwedenMain project: Kinetic modeling and molecular structure prediction in polymerization reactions
- Applied steered molecular dynamics, density functional theory, umbrella sampling, and metadynamics for reaction pathway exploration and free-energy profiling.
- Predicted crystal structures of molecular co-crystals and identified plausible reaction products from kinetics/thermodynamics.
- Coordinated multi-site collaborations on crystal structure prediction and lipid conformer analysis; advised students.
Education
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9/2017 – 5/2022PhD in Chemistry (Theoretical chemistry)Chalmers University of Technology, SwedenAward date 02/06/2022. Thesis: Nitriles in Prebiotic Chemistry and Astrobiology. Supervisor: Prof. Martin Rahm.
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8/2012 – 9/2017MEng in Chemical engineering with engineering physicsChalmers University of Technology, SwedenAward date 08/11/2017.
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8/2015 – 9/2017MSc in Engineering physics (Nanotechnology master program, integrated)Chalmers University of Technology, SwedenAward date 08/11/2017.
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8/2012 – 6/2015BSc in Chemical engineering with engineering physics (integrated)Chalmers University of Technology, SwedenAward date 12/06/2015.
Teaching
- Lectures and exercises
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2018–2020Quantum engineeringChalmers University of TechnologyComputer labs · 1st year MSc Nanotechnology · 2 h/week
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2018–2021Physical chemistryChalmers University of TechnologyTutorials and experimental labs · 2nd year BSc Biotechnology · 12 h/week
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2018–2021Theoretical chemistryChalmers University of TechnologyComputer labs · 3rd year BSc Chemical engineering · 4 h/week
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2017–2018Chemistry and biochemistryChalmers University of TechnologyExperimental labs · 1st year BSc Chemical engineering · 8 h/week
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2014CalculusChalmers University of TechnologyExercise sessions · 1st year BSc Chemical engineering · 1 h/week
- Pedagogical training
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2019Teaching, learning and evaluationChalmers University of Technology3 ECTS
- Supervision of students
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Since 2024Supervisor of MSc student — Aalto University
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Since 2024Advisor of PhD student — Aalto University
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Since 2022Co-supervisor of PhD student — University of Helsinki
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11/2024 – 5/2024Supervisor of BSc student — Aalto University
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5/2021 – 9/2021Co-supervisor of 2 visiting and 3 BSc students — Chalmers University of Technology
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1/2021 – 6/2021Co-supervisor of 6 BSc students — Chalmers University of Technology
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6/2020 – 8/2020Supervisor of 2 BSc students — Chalmers University of Technology
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1/2020 – 6/2020Supervisor of 6 BSc students — Chalmers University of Technology
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4/2019 – 7/2019Supervisor of visiting BSc students — Chalmers University of Technology
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4/2018 – 6/2018Supervisor of one BSc student — Chalmers University of Technology
Skills and Competences
- Programming
- Python, MATLAB, Bash — Well experienced
- Machine learning and cheminformatics
- Scikit-learn, TensorFlow, RDKit, OpenBabel, ASE — Experienced
- Molecular dynamics and simulation
- CP2K, GROMACS, PLUMED — Expert · xTB, QCxMS, VMD — Experienced
- High-performance computing (HPC)
- Parallel computing, cluster resource management — Experienced
- Version control
- Git — Experienced
- Languages
- Swedish (Excellent) · English (Excellent) · Italian (Intermediate) · French (Basic)
Awards and Honours
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2025Marie Skłodowska-Curie postdoctoral fellowship202,000 EUR
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2024–2025LUMI extreme scale access resource allocation
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2018–2021Travel grantsNils Philblad Foundation (2021) · Karl and Annie Leon's Foundation (2018–2019)
Academic Service
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2026Thesis reviewer and opponent — Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
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2025Reviewer for ACS Earth Space Chem, ACS Omega and Atmospheric Chemistry and Physics
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2025Organizing committee — Nordic Workshop on AI for Climate Change, Sweden
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2025Core member, organizer and Finland representative — Climate AI Nordics Network
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2024Panelist on AI in chemistry, physics, and education — FysKemDagarna
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2023Organizer of workshop hands-on session — Shaking Up Tech, Workshop for underrepresented groups in STEM, Aalto University, Finland
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2023Session chair and organizer — ESTML, Levi, Finland
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2022Session chair — AbSciCon, USA
Peer-Reviewed Publications
15 peer-reviewed articles, 6 first author. Total citations: 141, h-index: 5, i10-index: 5 — Google Scholar, updated 2 April 2026
- Cappelletti, M., Sandström, H., & Rahm, M. ACS Central Science, 12, 111–121 (2026). DOI: 10.1021/acscentsci.5c01497.
- Lind, L., Sandström, H., & Rinke, P. The Journal of Chemical Physics, 164 (2026). DOI: 10.1063/5.0308548.
- Madan, I., Aliabadi, S. A., Huhtasaari, J., Matic, E., Hogedal, E., Kamińska, K., Nilsson, F., Stark, A., Izquierdo-Ruiz, F., Sandström, H., Rahm, M. QRB Discovery, 6, e23 (2025). DOI: 10.1017/qrd.2025.10012. [Supervised students and co-created workflow for testing stability of polymers.]
- Brean, J., Bortolussi, F., Rowell, A., Beddows, D. C. S., Weinhold, K., Mettke, P., Merkel, M., Kumar, A., Barua, S., Iyer, S., Karppinen, A., Sandström, H., Rinke, P., et al. ACS ES&T Air, 2, 1704–1713 (2025). DOI: 10.1021/acsestair.5c00119. [Supervised PhD student F. Bortolussi in developing and evaluating the machine learning model and workflow.]
- Izquierdo-Ruiz, F., Cable, M. L., Hodyss, R., Vu, T. H., Sandström, H., Lobato, A., & Rahm, M. Proc. Natl. Acad. Sci. U.S.A., 122, e2507522122 (2025). DOI: 10.1073/pnas.2507522122. [Developed and tested crystal structure prediction program workflow for molecular cocrystals.]
- Valiev, R. R., Nasibullin, R. T., Sandström, H., Rinke, P., Puolamäki, K., & Kurten, T. Physical Chemistry Chemical Physics, 27, 14804–14814 (2025). DOI: 10.1039/D5CP01101A. [Co-advisor for ML workflow; developed MBTR model.]
- Bortolussi, F., Sandström, H., Partovi, F., Mikkilä, J., Rinke, P., & Rissanen, M. Atmospheric Chemistry and Physics, 25, 685–704 (2025). DOI: 10.5194/acp-25-685-2025. [Co-designed study, advised, and contributed to programming and model testing.]
- Malaska, M. J., Sandström, H., Hofmann, A. E., Hodyss, R., Rensmo, L., van der Meulen, M., Rahm, M., Cable, M. L., & Lunine, J. I. Astrobiology, 25, 367–389 (2025). DOI: 10.1089/ast.2024.0125. [Performed geometry optimizations, conformer search and student supervision.]
- Sandström, H., & Rinke, P. Geoscientific Model Development, 18, 2701–2724 (2025). DOI: 10.5194/gmd-18-2701-2025.
- Sandström, H., Rissanen, M., Rousu, J., & Rinke, P. Advanced Science, 11, 2306235 (2024). DOI: 10.1002/advs.202306235.
- Sandström, H., Izquierdo-Ruiz, F., Cappelletti, M., Dogan, R., Sharma, S., Bailey, C., & Rahm, M. ACS Earth and Space Chemistry, 8, 1272–1280 (2024). DOI: 10.1021/acsearthspacechem.4c00088.
- Sandström, H., & Rahm, M. The Journal of Physical Chemistry A, 127, 4503–4510 (2023). DOI: 10.1021/acs.jpca.3c01504.
- Sandström, H., & Rahm, M. ACS Earth and Space Chemistry, 5, 2152–2159 (2021). DOI: 10.1021/acsearthspacechem.1c00195.
- Sandström, H., & Rahm, M. Science Advances, 6, eaax0272 (2020). DOI: 10.1126/sciadv.aax0272.
- Lindblom, A., Sriram, K. K., Müller, V., Öz, R., Sandström, H., Åhrén, C., Westerlund, F., & Karami, N. Diagnostic Microbiology and Infectious Disease, 93, 380–385 (2019). DOI: 10.1016/j.diagmicrobio.2018.10.014. [Performed fluorescence microscopy assays where I stained, trapped, and photographed plasmids in nanochannels.]
Talks
- Invited seminars and keynotes
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2026Data-driven compound identification with atmospheric mass spectrometryNetwork on Mathematical Data Science for Materials Science, Workshop on the Interface of Mathematics and Machine Learning for Applications in Materials Science — University of Glasgow, UK
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2025CLOUDMAP – Advanced identification of atmospheric compoundsAtmospheric day, Sweden — Keynote
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2025Machine learning for atmospheric mass spectrometryNordic Workshop on AI for Climate Change, Sweden
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2024AI in Chemistry: Solving experimental challenges with artificial intelligenceFysKemDagarna (Physics and Chemistry Days), Sweden
- Contributed talks
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2026Towards atmospheric compound identification using simulated electron ionization mass spectraChemical Compounds Space Conference (CCSC 2026), Munich, Germany
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2023Characterizing Atmospheric Molecules for Machine LearningInternational Aerosol Modeling Algorithms Conference, USA
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2023Characterizing Atmospheric Molecules for Machine LearningEuropean Aerosol Conference, Spain
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2023Characterizing atmospheric molecules for machine learningPhysics Days, Finland
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2022Untangling hydrogen cyanide polymerization using quantum chemistryAbSciCon, USA