Promovendus Moleculaire Microbiologie

Het onderzoek in BlueVantage is verdeeld over verschillende thematische werkpakketten. Deze promotieplek maakt deel uit van werkpakket 4 (industrieel afvalwater) waarin je onderzoekt of schimmels gebruikt kunnen worden om moeilijk afbreekbaar lignocellulose af te breken met behulp van schimmelbioreactoren. Je werkt hierbij zowel binnen de groep Moleculaire Microbiologie van de Universiteit Utrecht als binnen de Milieutechnologie groep van Wageningen Universiteit & Research. Daarnaast sta je in nauw contact met eindgebruikers. Je werkzaamheden bestaan in het bijzonder uit:

• Je analyseert de afbraak van lignocellulose afvalstromen door met name paddenstoelvormende schimmels, al dan niet in een consortium met andere schimmels en bacteriën.
• Je bestudeert de mechanismen die aan de afbraak van het lignocellulose ten grondslag liggen.
• Je ontwikkelt een bioreactor die grootschalige afbraak van lignocellulose in afvalwater door geselecteerde schimmels /consortia mogelijk maakt.
• Je schrijft rapporten en artikelen over je onderzoek, die leiden tot een proefschrift, en presenteert je onderzoek binnen BlueVantage en op (inter)nationale congressen.
• Je neemt deel aan BlueVantage activiteiten, zoals consortium bijeenkomsten, workshops en stakeholder interacties, en volgt daarnaast relevante cursussen.
• Je draagt bij aan het onderwijs binnen de Nederlandstalige Biologie bachelor en de Engelstalige masteropleiding Biosciences van de Universiteit Utrecht

Anthropology Lecturer

The teaching responsibilities primarily include giving lectures and conducting seminars across various courses offered by the Anthropology track, grading assignments and exams, (co-)redesigning a course, and supervising students during their thesis writing process within the Anthropology and (where possible) Political Sciences track.

Furthermore, you will participate in student matching and outreach activities, and contribute to maintaining the quality of the track programme within the teaching team.

PhD Position in Human Data Interaction for Health and Wellbeing

Digital technologies, such as wearables and mobile applications, allow individuals to continuously track personal data related to health and wellbeing. These systems capture a wide range of metrics, including steps taken, stress levels, heart rate, and sleep quality. Metrics are not neutral entities: they shape self-perception, evoke emotion, and can reinforce social norms, often surfacing sensitivities, taboos, and stigma. As a result, people’s experiences with their data are shaped not only by usability, but by how these metrics are interpreted, felt, and situated within everyday life; often involving processes of reflection and, at times, rumination.

In this PhD project, you will investigate the lived and affective experience of personal data in context. The focus is on how individuals interpret and engage with their metrics over time, particularly when these data become emotionally charged or socially sensitive. You will examine how such experiences influence ongoing interaction, including responses such as reflection, discomfort, reassurance, or resistance.

The project takes a human-centred and interpretive perspective, drawing on concepts from human-computer interaction, sociology, and psychology. It focuses on meaning-making and subjective experience, contributing to research in human-data interaction and personal informatics by examining how data is experienced, negotiated, and sometimes avoided in everyday contexts.

Methodologically, you will make use of qualitative and design-oriented approaches, such as interviews, ethnographies, diary studies, and reflective or speculative design. You will also investigate the design of reflection-supportive systems that scaffold how and when people engage with their metrics, with attention to supporting reflection while avoiding rumination.

You will have the opportunity to shape specific research directions within this theme, including data sensitivity, affective responses to metrics, and the role of social and cultural norms in human-data interaction. The project aims to produce high-quality academic publications as well as insights that inform the design of technologies that better account for the social, cultural, and experiential dimensions of human-data interaction.

You will contribute to teaching activities within the department, providing you with the opportunity to further develop your teaching skills (approximately 15% of your time).

Docent Psychologische Functieleer

Als Docent ga je voornamelijk werkgroepen geven, opdrachten en tentamens nakijken, en practica en theses/stages begeleiden. Deze werkzaamheden vallen binnen de bacheloropleiding Psychologie en andere opleidingen waar de afdeling psychologische functieleer aan bijdraagt. Dat zijn de BSc Kunstmatige Intelligentie, Utrecht University College, MSc Neuropsychology, MSc Applied Cognitive Psychology, MSc Artificial Intelligence en/of MSc Neuroscience & Cognition.

De precieze onderwijstaken zijn afhankelijk van de expertise en competenties die jij als docent meebrengt, waarbij we ervan uitgaan dat thesisbegeleiding in bachelor en master in ieder geval tot de taken zal behoren. Daarom is een afgeronde of bijna afgeronde promotie noodzakelijk. We vinden het ook belangrijk dat je als docent deelneemt aan onderzoeksgroepen van de afdeling waar samenwerking plaatsvindt op onderzoeksprojecten. Naast je taken als docent is er in overleg ook de mogelijkheid om tijdelijk wat onderzoekstaken uit te voeren.

PhD Position in Analytical Chemistry

You will work in an analytical laboratory equipped with advanced instrumentation, including (2D-)LC, CE, and several ion mobility-mass spectrometry (IM-MS) platforms. The project aims to achieve reliable structural identification and quantification of glycans and glycopeptides in complex biological samples, including cell surfaces and tissue sections, using high-resolution (HR) IM-MS techniques. For instance, you will investigate MS fragmentation methods and utilize various glycan labeling strategies to examine their gas-phase conformations. Furthermore, you will develop calibration techniques to accurately determine collision cross-sections (CCS) for HR IM-MS platforms.

Your responsibilities include:

• Developing, optimizing, and applying analytical methods (e.g., 2D-LC-IM-MS).
• Designing experiments to characterize glycan structures in biological samples.
• Interpreting complex datasets and translating findings into biological insights.
• Collaborating with chemists, biologists, and pharmaceutical scientists.
• Sharing your results through scientific publications and presentations at (inter)national conferences.

This position offers strong opportunities to develop expertise in advanced analytical chemistry and interdisciplinary research.