Research Assistant

Offer Description

The University of Bucharest is announcing a competition to fill a position for a research assistant, COR code 263306, within the project “Center of Excellence for Climate and Societal Change,” project code PN-IV-P6-6.1-CoEx-2024-0042, funded by UEFISCDI.

Employment period: fixed-term – December 31, 2027

Work schedule - 4 hours/day.

Where to apply

E-mail: concursuri@hr.unibuc.ro

Requirements

Research Field: Philosophy » Other

Education Level: PhD or equivalent

Skills/Qualifications

• Ph.D. student in the field of Philosophy.
• Programming skills (e.g., Python), demonstrated through projects, publications, a portfolio, or professional experience.
• Skills in artificial intelligence / machine learning
• Skills in psychophysiological data acquisition
• Knowledge of biological signal processing: filtering, artifact detection and removal, independent component analysis (ICA), feature extraction.
• Knowledge of research methodology in the social and behavioral sciences (experimental design, data collection, and data management).
• Communication and interpersonal skills for interacting with study participants.
• Knowledge of English at a level sufficient to work with the scientific literature.

Specific Requirements

Job Responsibilities:

• Contribute to the design and implementation of experiments.
• Program and automate experimental protocols (stimulus presentation, data collection).
• Acquire psychophysiological data in the laboratory.
• Pre-process and analyze signals (filtering, artifact detection, ICA, feature extraction).
• Developing, training, and evaluating machine learning models for behavioral and physiological data.
• Managing, cleaning, and documenting datasets.
• Complying with ethical protocols and personal data protection regulations.
• Contributing to the drafting of research reports and publications.

Languages: ENGLISH — Level: Good

Languages: ROMANIAN — Level: Mother Tongue

Research Field: Philosophy » Other

Years of Research Experience: 1 - 4

Additional Information

Benefits

Topics:

1. Psychophysiological data acquisition: principles of electroencephalography (EEG) and electrodermal activity (EDA) measurement; setup, acquisition systems, signal quality.
2. Preprocessing of psychophysiological signals: filtering, segmentation, artifact detection and removal, independent component analysis (ICA) for EEG; decomposition of EDA into tonic and phasic components (electrodermal responses).
3. Feature extraction and signal analysis.
4. Programming for experimental research: Python and specialized libraries; stimulus presentation (e.g., PsychoPy); automation of data workflows.
5. Machine learning / artificial intelligence for behavioral and physiological data.
6. Research methodology in behavioral and environmental psychology; data management and cleaning.
7. Ethical considerations in research involving human participants; protection of personal data (GDPR).

Eligibility criteria

Bibliography:

• American Psychological Association (2017). Ethical Principles of Psychologists and Code of Conduct. https://www.apa.org/ethics/code
• Boucsein, W. (2012). Electrodermal activity (2nd ed.). Springer Science + Business Media. https://doi.org/10.1007/978-1-4614-1126-0
• Brunet, D., Murray, M. M., & Michel, C. M. (2011). Spatiotemporal analysis of multichannel EEG: CARTOOL. Computational Intelligence and Neuroscience, 2011, 813870. https://doi.org/10.1155/2011/813870
• Delorme, A., & Makeig, S. (2004). EEGLAB: an open-source toolbox for the analysis of single-trial EEG dynamics, including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009
• Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
• Gramfort, A. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7. https://doi.org/10.3389/fnins.2013.00267
• Makowski, D., Pham, T., Lau, Z. J., Brammer, J. C., Lespinasse, F., Pham, H., Schölzel, C., & Chen, S. H. A. (2021). NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior Research Methods, 53(4), 1689–1696. https://doi.org/10.3758/s13428-020-01516-y
• Michel, C. M., & Koenig, T. (2018). EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review. NeuroImage, 180(Pt B), 577–593.
• World Medical Association (2013). Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA, 310(20), 2191–2194.

Selection process

Competition stages:

1. Review of application materials
2. Written exam
3. Interview.

Additional comments

If you have any questions, please feel free to contact us by email at Prof. Iuliana Armaș, Ph.D., project manager: iulia_armas@geo.unibuc.ro

Website for additional job details: https://unibuc.ro/despre-ub/cariere/posturi-cercetare/#1544693602256-6d9237ad-7fe3

Work Location(s)

Number of offers available: 1

Company/Institute: Universitatea din Bucuresti - Rectorat

Country: Romania

State/Province: Bucharest

City: Sector 5

Postal Code: 050663

Street: Sos Panduri 90

Contact

State/Province: Bucharest

City: Bucharest

Website: http://www.unibuc.ro/n/despre/

Street: Soseaua Panduri, no. 90

Postal Code: 050663

E-Mail: office@g.unibuc.ro

Phone: 021.305.97.30