Eindhoven, North Brabant, Netherlands
As a Senior Project Manager within ASML R&D for both EUV and DUV, I possess six years of post-PhD industry experience, specializing in the deployment of advanced technologies for semiconductor lithography systems. I coordinate complex cross-sector and cross-platform projects at all stages, from initial technological feasibility assessments to full-scale production and consecutive field support. My leadership extends to seven multi-disciplinary international core teams, navigating in highly dynamic and technically challenging product environments. I am adept at managing escalations involving customers, internal stakeholders, and suppliers. A strong technical foundation combined with analytical and innovative capabilities leads me to address a wide range of technology challenges and contribute to various cross-sector strategic roadmaps. Combined with strong interpersonal skills, this enables me to rapidly acquire new knowledge and develop strategies which are aligned with both business objectives and technological goals. Furthermore, I establish effective multi-level reporting structures within the organization to facilitate informed decision-making processes.
Engineering Manager in the role of Team Leader and Project Leader for Referencing Wafers within Development and Engineering. Escalation lead. Development of products for DUV, EUV, and Applications business lines. Responsible for repository management and code quality at group level as well as co-responsible for a large company-wide repository.
I contributed to developing, testing, implementing, and industrializing overlay references for photolithography equipment. Optimizing and analyzing machine overlay performance through a combination of mathematical and statistical models. Development of data analysis software and toolboxes. Responsible for repository management and code quality at group level as well as co-responsible for a large company-wide repository. Third line escalation support.
PhD research looking into how the human brain separates multiple simultaneously present sounds in our environment into distinct entities which can be perceived separately, namely Auditory Scene Analysis. More specifically, I employed polyphonic music to study this phenomenon. In order to investigate these mechanisms, I mostly used ultra-high field functional Magnetic Resonance Imaging at 7 Tesla. For the analysis of such high-resolution and high-dimensional data we acquired in our paradigm(s), I made use of, and worked on applying to neuroimaging data, a multitude of analysis methods such as machine learning, bayesian inference, and blind source separation. Aside from the application of cutting-edge analysis methods I custom developed most of the software employed in the analysis of such data. For a more detailed overview of my previous research, please visit my personal webpage: www.nielsdisbergen.net
Research master in Cognitive Neuroscience at Maastricht University. Specialization with a focus on neuro imaging methods (e.g. fMRI, EEG, TMS) and data processing. Graduated with highest honors (Cum Laude). Personal interest: Auditory Neuroscience and Multivariate Analysis Methods for fMRI Dissertation title: "Streaming Music in the Brain: The engagement and attentive modulation of auditory stream segregation with polyphonic music"
Research assistant at the Faculty of Psychology and Neuroscience, department of Cognitive Neuroscience. Studying cortical auditory mechanisms for early sensory-perceptual transformations with multivariate classification methods. Further focus on Matlab programming for the analysis of neuroimaging data.
Research exchange to Prof. Zatorre's lab on a scholarship from the Erasmus Mundus Exchange Network in Auditory Cognitive Neuroscience. The exchange was undertaken to further develop those projects I collaborate on with the Zatorre lab.
Research internship as part of the research master program in Cognitive Neuroscience at Maastricht University. Research development, implementation, and analysis of auditory scene analysis assessed with music and multivariate analysis of fMRI data.
Lab visit to the group of Prof. Dr. Charles E. Schroeder at Columbia University, New York City. Research Assistantship on Audio-visual recalibration measured with Electrocorticography (ECoG) in epileptic patients.