Scientific Researcher - Neuroscience, Erasmus MC Rotterdam

Scientific Researcher - Neuroscience, Erasmus MC Rotterdam

Scientific Research
Rotterdam
Netherlands
Erasmus Medical Centre Rotterdam
Research Position (Pre-PhD)

Scientific Researcher Erasmus MC / neuroscience

[Summary]
The scientific backbone of BfNA / cerebellar prediction, sensorimotor learning and brain-environment adaptation.
[Team]
Supervisor: Prof. Chris de Zeeuw (INF Rotterdam / KNAW)
[Neural Tags]

Pre-PhD research position · LAS Article 9

[Description]

Fundamental Research in Neuroscience. Speciality: Fundamental Physiology / Neuroanatomy / Tracer injections + Immunohistology + Confocal microscopy. Research focus: Bidirectional Cerebellar Control of Everything / Brain enhancement through environment / Neuroanatomical studies in relation to movement. Pre-PhD programme: Erasmus MC Academie. Laboratory Animal Science (LAS) - Article 9, Universiteit Utrecht (2020).Fundamental neuroscience research. Cerebellar control and brain-environment interaction. Pre-PhD.

[Key Figures]

Typology: Scientific Research · 3.5 years · Lab: Dept. Neuroscience, Erasmus MC · Supervisor: Prof. Chris de Zeeuw (KNAW member) · Methods: tracer injections + immunohistology + confocal microscopy · Pre-PhD: Erasmus MC Academie · LAS Article 9 certification (Utrecht, 2020)

[Neural Analysis]

SCIENTIFIC BACKBONE: The Erasmus MC research period forms the empirical hinge between architecture and neural science: cerebellar timing, prediction, motor learning and environmental adaptation become the methodological ground for later BfNA / HEI work.

CEREBELLAR PREDICTION [M1][M2][S2]: This row is the strongest scientific foundation in the archive. De Zeeuw & Ten Brinke (2015) position cerebellar modules as learning systems with differentiated encoding schemes; Hull (2020) extends cerebellar circuits beyond supervised motor correction towards prediction; Schmahmann's cerebellar cognitive affective syndrome literature supports the cerebellum's role in cognition and affect beyond movement. For BfNA, this matters because architecture is not read as stimulus decoration, but as a field of prediction, timing, locomotion and correction. The built environment becomes a laboratory outside the laboratory.

[Social Impact]

SOCIAL: Direct social impact through HEI - translating fundamental neuroscience into CSRD-compliant (ESRS S1) metrics for built environment social reporting. The missing link between architecture and evidence-based social impact measurement.

[ROI Sustainability]

ROI: HEI is the direct commercial return on this research investment. The scientific credibility of Erasmus MC research is the primary competitive differentiator of HEI vs. any other built environment measurement tool. SUSTAINABILITY: Brain health IS sustainability - the most fundamental human resource. HEI measures the environmental determinants of cognitive capital.

[Applied R&D Lens]

Translate cerebellar prediction, locomotor anticipation and sensorimotor correction into protocols for measuring built-environment adaptation outside the laboratory.