Softwareontwikkelaar

Functieomschrijving
Als Softwareontwikkelaar word je onderdeel van de afdeling Instrumentation Engineering binnen de Faculty of Psychology and Neuroscience aan Maastricht University. Ons team ontwikkelt geavanceerde softwareapplicaties en technische oplossingen die worden ingezet in wetenschappelijk onderzoek naar gedrag, cognitie en hersenprocessen, daarnaast worden onze oplossingen ook toegepast in het onderwijs binnen onze faculteit. We ondersteunen onderzoekers met innovatieve technologieën, waardoor experimenten efficiënter, nauwkeuriger en veelzijdiger worden uitgevoerd.

Je werkt aan veel verschillende projecten, variërend van dataverzameling en -analyse, real-time verwerking van neurofysiologische signalen en integratie van hardware- en softwareoplossingen voor experimenteel onderzoek. We maken gebruik van een breed scala aan programmeertalen en technologieën, afgestemd op de specifieke behoeften van elk onderzoeksproject.

Je werkt zelfstandig of in teamverband, waarbij je de volledige ontwikkelcyclus van eerste aanvraag tot eindoplevering en ondersteuning doorloopt. Je taken variëren van het ontwikkelen van webapplicaties, databases en backend API’s, tot het werken aan hardware-interfacing en het ontwikkelen van apps. Je werkt in teamverband en hebt de vrijheid om creatieve en innovatieve oplossingen aan te dragen.

Je komt terecht in een stimulerende, academische omgeving waar technologie en wetenschap samenkomen. Instrumentation Engineering is een klein, maar dynamisch team dat nauw samenwerkt met onderzoekers, promovendi en andere technische specialisten.

Wat ga je doen?

• Ontwikkeling, ondersteuning en implementatie van softwareoplossingen van eerste aanvraag tot eindoplevering.
• Ontwerpen en bouwen van webapplicaties, databases en backend API’s.
• Ontwikkeling en ondersteuning van apps.
• Ontwikkeling en ondersteuning van hardware-interfacing en elektronische toepassingen.
• Ontdekken welke rol AI kan spelen in je eigen werk en in het onderzoek van FPN.

Voor meer informatie over afdeling Instrumentation Engineering klik hier.

Wat bieden wij?

• Een uitdagende functie met gevarieerde projecten.
• De kans om je skills te ontwikkelen op het gebied van zowel soft- als hardware.
• Mogelijkheden om te werken met innovatieve technologieën zoals AI/Machine learning.
• Een prettige en informele werkomgeving met veel ruimte voor eigen initiatief.

Functie-eisen

• Je hebt minimaal een afgeronde hbo-opleiding in ICT of in een gerelateerd vakgebied, liefst met enige jaren werkervaring. We moedigen iedereen aan om te solliciteren, of je nu net klaar bent met je studie of al wat ervaring hebt.
• Kennis van webontwikkeling, databases en backend API’s.
• Je schakelt moeiteloos tussen verschillende programmeertalen en technologieën.
• Je hebt affiniteit met hardware-interfacing en elektronica.
• Ervaring of interesse in PCB-ontwerp, AI/machine learning en online security is een pré.
• Je bent een ondernemende teamplayer, zelfstandig, creatief en resultaatgericht.
• Ervaring met de Agile werkwijze.
• Goede mondelinge en schriftelijke communicatievaardigheden in het Nederlands en het Engels.
• Kwaliteiten om meerdere ballen tegelijk in de lucht te houden.
• Je bent bereid om jezelf te blijven ontwikkelen.

Een meeloop dagdeel is onderdeel van de sollicitatieprocedure.

Software developer

Job Description
As a software developer, you will become part of the Instrumentation Engineering department within the Faculty of Psychology and Neuroscience at Maastricht University. Our team develops advanced software applications and technical solutions used in scientific research on behavior, cognition, and brain function. Our solutions are also applied in education within our faculty. We support researchers with innovative technologies, making experiments more efficient, accurate, and versatile.

You will work on various projects, ranging from data collection and analysis to real-time processing of neurophysiological signals and integrating hardware and software solutions for experimental research. We use a wide range of programming languages and technologies, tailored to the specific needs of each research project.

You will work independently or as part of a team, covering the full development cycle from initial request to final delivery and support. Your tasks will vary from developing web applications, databases, and backend APIs to working on hardware interfacing and app development. You will be part of a team and can suggest creative and innovative solutions.

You will work in a vibrant academic environment where technology and science come together. Instrumentation Engineering is a small but dynamic team that closely collaborates with researchers, PhD students, and other technical specialists.

What will you do?

• Develop, support and implement software solutions from initial request to final delivery.
• Design and build web applications, databases, and backend APIs.
• Develop and support apps.
• Develop and support hardware interfacing and electronic applications.
• Explore how AI can be applied in your work and in research at FPN.

For more information about the Instrumentation Engineering department, click here.

What do we offer?

• A challenging role with a variety of projects.
• The opportunity to develop your skills in both software and hardware.
• The chance to work with innovative technologies such as AI/Machine Learning.
• A pleasant and informal working environment with plenty of room for initiative.

Job Requirements

• A completed Bachelor or higher degree in ICT or a related field of work, preferably with some work experience. We encourage everyone to apply, whether you are a recent graduate or have some experience.
• Knowledge of web development, databases, and backend APIs.
• Ability to switch effortlessly between different programming languages and technologies.
• Affinity with hardware interfacing and electronics.
• Experience or interest in PCB design, AI/Machine Learning, and online security is a plus.
• You are a team player who is independent, creative, and results-oriented.
• Experience with Agile methodologies.
• Good verbal and written communication skills in both Dutch and English.
• Ability to manage multiple tasks simultaneously.
• Willingness to continuously develop yourself.

As a trial, half a workday is part of the application procedure.

PhD candidate to conduct ethnographic research on smart farming

Job Description

Smart farming refers to the use of digital technologies to automate various agricultural practices ranging from planting to the application of fertilizers and pesticides to harvesting, and it is an increasingly important area of both public and private investment. Although smart farming is often pitched as enhancing productivity and increasing yields, anthropologists and political ecologists have recently begun to identify the role these technologies play in shifting the power relations between farm workers, farm managers, and investors, while also changing the practices of agriculture and their environmental impacts. Advances in sensor technology, robotics and artificial intelligence are leading to the datafication, digitalization, and automation of agricultural production in ways that are at once both novel and part of a much longer history of the political economy and ecology of changing agricultural technologies.

Drawing on case studies in the Netherlands and/or Flanders, the PhD researcher will undertake in-depth ethnographic research among people involved in the development, promotion, and use of smart farming technologies, with a particular emphasis on the perspectives and experiences of farmers and their role in these interconnected processes.

Through an analysis of the cases, the project will explore the role that digital technologies play in the spatial, temporal and cultural mediation of agricultural landscapes and the actors who inhabit them. In collaboration with the supervision team, the PhD researcher will study sustainability discourses around digital technologies in agriculture and the promises and expectations, future visions, hopes and fears attributed to them by key actors (such as farmers and farm workers, policy makers, tech companies, etc). Furthermore, this project takes an interest in how the past, present and future are (discursively) connected in the current practices of embedding digital technologies in agriculture: how may existing ways of organizing and doing agriculture ‘clash’ with new practices that follow from the embedding of digital technology, and how do people working in the agricultural sector engage with these technologies?

Requirements
The position is open to candidates with backgrounds in STS, anthropology and/or human geography with experience developing and carrying out qualitative research projects. Proficiency in Dutch is preferred. The PhD candidate will be supervised by Dr. Matthew Archer (primary supervisor) and Prof. Dr. Anique Hommels (promotor) and will be based in the Department of Society Studies and the Maastricht University STS (MUSTS) research group.

The PhD candidate will be expected to design and carry out an ethnographic research project on smart farming in the Netherlands and/or Belgium, which will form the basis of the dissertation.

Docent Toetsing, Onderwijsontwerp en E-learning

Functieomschrijving

Als docent weet je andere docenten te motiveren voor onderwijsinnovatie, vervul je onderwijsrollen en doe je onderzoek op dit terrein. Het onderzoek vindt plaats binnen de School of Health Professions Education (SHE) in nauwe afstemming met de Vakgroep O&O. Tot jouw taken behoren:

• Bijdragen aan de implementatie van genAI en portfolio’s in de opleidingen van de FHML op basis wetenschappelijke en maatschappelijke inzichten;
• Het ontwikkelen en verzorgen van trainingen over AI-gebruik om onderwijs en toetsing effectief en efficiënt te ontwerpen;
• Het verzorgen van trainingen en ondersteuning rondom de nieuwe portfoliosystemen;
• Het uitvoeren van onderwijsrollen binnen verschillende opleidingen van de FHML;
• Het verrichten van wetenschappelijk onderzoek op het gebied van bovengenoemde taken, resulterend in (inter)nationale publicaties.

Functie-eisen:

Als verbinder en teamwerker ben in je staat docenten te inspireren om op een innovatieve manier les te geven. Je bent communicatief sterk en beschikt over organisatietalent. Verder voldoe je aan de volgende functie-eisen:

• Je beschikt over een afgeronde masteropleiding, bij voorkeur in de onderwijswetenschappen/onderwijspsychologie of een ander relevant domein;
• Je bent gepromoveerd op een relevant onderwerp;
• Je beschikt over een BKO-certificaat;
• Je hebt ervaring met het ontwikkelen en geven van onderwijs bij voorkeur binnen student-gecentreerd onderwijs;
• Bij voorkeur heb je ervaring als onderwijskundig adviseur in het hoger onderwijs en met het leiden van projecten;
• Beschik je over onderzoekskwaliteiten, blijkend uit wetenschappelijke publicaties en;
• Beheers je de Nederlandse én Engelse taal in woord en geschrift.

Postdoc in patterns of physical activity and health

Job Description
From recent research we know that not only moderate-intensity activities improve health, but that reducing sitting is an important factor too. Yet health promoting guidelines still only focus on those activities. We believe that a healthy pattern of physical activity behaviour is determined by the combination of duration, frequency, and intensity of activities, and that multiple healthy combinations might exist for each individual or population. Unravelling what constitutes an optimal profile, might contribute to personalized physical activity behaviour recommendations, and thus enable tailored lifestyle coaching, with potentially larger and more sustainable effects on health. Funded by NWO, this project will aid the shift from the current approach ‘one physical activity guideline for all’ to an approach in which we promote an active lifestyle via tailoring ‘each determines their activity goals’.

For our team of movement, data, and health promotion scientists, we are looking for a postdoc to delve deeper into patterns of physical activity behaviour. Based on an ongoing descriptive systematic review by our research team about the definitions and calculations of currently used pattern characteristics, you will systematically review the relationship of these patterns characteristics with health markers. In a next step, you will analyse physical activity behaviour and health in detail in a large, existing cohort data set, applying Machine Learning techniques to handle the intricate structure and possible co-dependency of variables.
Alongside the postdoc project, a research line led by the PI focuses on the translation of patterns into lifestyle coaching. The postdoc and PI will collaborate to create and integrate the two lines of research.

Your key responsibility include:

• Perform and coordinate a systematic review examining the relationship between physical activity metrics and cardiometabolic health.
• Collaborate with a PhD student to create an overview of relevant physical activity pattern characteristics to study in detail in existing cohort data.
• Collaborate with PIs and a PhD student to program the data processing and calculations of physical activity pattern characteristics in cohort data.
• Statistical analyses of cohort data to study the association of physical activity pattern characteristics with cardiometabolic health markers.
• Collaborate with PIs and collaborators to translate scientific knowledge to education/practice.
• Dissemination activities, like publications and conference presentations, and communication within collaborations.
• Educate in programmes of Human Movement Sciences, Biomedical Sciences and/or Health Sciences.

Requirements
Our ideal candidate holds a PhD in Movement Sciences, Health Sciences, Health Promotion, Epidemiology, or related field. Additionally, we are looking for:

• Experience with physical activity measurement, interventions, processing and/or analyses.
• Experience with systematic reviewing, and preferably also experience with meta-analysis.
• Affinity with physical activity monitoring.
• Affinity with biomarker and physiological health data.
• Affinity with, or experience with, data sciences, machine learning, and data mining techniques.
• Willingness to play an active role in education, aligned with research topic.