Internship/Master project: Advanced Microscopy of Basal Inhibitory Signaling

Work Activities
Visualizing Basal Inhibitory Signaling in T Cells Using Advanced Microscopy
Are you curious about how immune cells make life-or-death decisions? Do you want to explore the molecular tug-of-war between activation and inhibition in real time? Join us in the Physics of Cellular Interactions (PCI) group, led by Dr. Kristina Ganzinger, to investigate how inhibitory immune receptors like PD-1 suppress T cell activation.

In this project, you will use cutting-edge microscopy techniques to visualize the molecular dynamics of immune signaling. You will explore how PD-1, a key inhibitory receptor, can suppress T cell signaling through basal activity, and how novel therapeutic molecules - called RIPR molecules - can reverse this basal inhibition and have more potent effects.
Understanding and proving the existence of basal PD-1 signaling is crucial, as it may explain why many cancer patients do not respond to current PD-1/PD-L1 checkpoint blockade therapies. By uncovering this hidden layer of immune suppression, your work could help guide the development of more effective treatments that potentiate T cell activity against tumors.

More About the Project
T cells are activated when their T cell receptors (TCRs) bind to peptide-MHC (pMHC) complexes, triggering a phosphorylation cascade involving kinases like LCK and adaptor proteins like Zap70. However, this activation can be suppressed by inhibitory receptors such as PD-1, which recruit phosphatases like SHP1/2 to dephosphorylate key signaling proteins.

Recent studies suggest that PD-1 may exert basal inhibitory activity, even in the absence of its ligand PD-L1. This project aims to test that hypothesis using supported lipid bilayers (SLBs) and single-molecule fluorescence microscopy. You will:

• Reconstitute TCR and PD-1 signaling of cells on SLBs functionalized with pMHC and PD-L1.
• Measure Zap70 and SHP2 activity using total internal fluorescent (TIRF) microscopy.
• Compare how RIPR molecules - which recruit the phosphatase CD45 to PD-1 - can suppress PD-1 activity and restore TCR signaling.

This work is part of the REPRESSIT consortium (https://www.repressit.eu/), a European collaboration developing next-generation immunotherapies that go beyond traditional checkpoint inhibitors.

What You Will Learn

1. Preparation of functionalized supported lipid bilayers (SLBs).
2. Use of TIRF and single-molecule microscopy to study protein dynamics.
3. Quantitative analysis of spatiotemporal signaling patterns.
4. Insight into the biophysics of immune regulation and therapeutic design.

Background Reading

1. Fernandes, R.A., et al. Immune receptor inhibition through enforced phosphatase recruitment. Nature (2020).
2. Davis, S., et al. The kinetic-segregation model: TCR triggering and beyond. Nat Immunol. (2006).
3. Wei, S.C., et al. Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discovery (2018).

Qualifications
You are currently enrolled in a Master’s program in (bio)physics, molecular biology, biomedical sciences, or a related field. You have a nationality of an EU-member state and/or you are a student at a Netherlands University. The internship has to be a mandatory part of your curriculum. We expect you to be available for at least 6 months, although longer is preferable.

Work environment
AMOLF is a part of NWO-I and initiate and performs leading fundamental research on the physics of complex forms of matter, and to create new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl

Physics of Cellular Interactions (Ganzinger) group –We are a supportive and social research group of about 8 PhD students and postdocs, which work together in small teams on various projects from immunological signalling to signalling in synthetic cells. The collaborative and social atmosphere includes to the other research groups at the AMOLF institute at the Science Park in Amsterdam. Our group has been making recent technical advances, including a new single-molecule tracking method based on DNA-PAINT that we recently developed (Nat Commun 2021, Nat Commun 2023), new in vitro assays (ACS Syn Biol 2021, ACS Omega 2024), and imaging approaches developed by our lab and others (JACS 2013, Nat Immun 2016, PNAS 2019), all to closely investigate the intricate molecular details of cellular signaling.

https://amolf.nl/research-groups/physics-of-cellular-interactions

Working conditions
At the start of the traineeship your trainee plan will be set out, in consultation with your AMOLF supervisor.

More information?
For further information about the position, please contact Gerard Castro-Linares g.castrolinares@amolf.nl or Kristina Ganzinger: k.ganzinger@amolf.nl.

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

PhD-student: Computing and Learning with Material Bits

Work Activities
We are seeking a motivated PhD - student to join our team working on the theory of computing and learning in physical systems, as part of a joint theoretical/experimental program on Smart Materials for Information Processing.

With increasing demands on computing and its accompanying energy consumption, there is a pressing need for alternatives to conventional computing hardware. In this project you will investigate and develop novel design and learning strategies for computing based on networks of bistable physical elements. This work is based on recent breakthroughs in our groups. The Van Hecke group has developed techniques for in-materia computing using interacting material bits named hysterons1,2, and the Stern Group has introduced strategies for self-learning materials inspired by ideas from machine learning and neuroscience3,4. Here we aim to join these ideas, in the context of networks of multistable electronic components as developed by experimental colleagues at Twente University5-7. This is a highly ambitious program with 3 PhD - positions (one at AMOLF, two at Twente), in which we aim to establish an exciting new paradigm for computing and learning, and demonstrate it in the lab.

We are seeking a motivated PhD - student to join our team working on the theory of computing and learning in physical systems, as part of a joint theoretical/experimental program on Smart Materials for Information Processing.

With increasing demands on computing and its accompanying energy consumption, there is a pressing need for alternatives to conventional computing hardware. In this project you will investigate and develop novel design and learning strategies for computing based on networks of bistable physical elements. This work is based on recent breakthroughs in our groups. The Van Hecke group has developed techniques for in-materia computing using interacting material bits named hysterons1,2, and the Stern Group has introduced strategies for self-learning materials inspired by ideas from machine learning and neuroscience3,4. Here we aim to join these ideas, in the context of networks of multistable electronic components as developed by experimental colleagues at Twente University5-7. This is a highly ambitious program with 3 PhD - positions (one at AMOLF, two at Twente), in which we aim to establish an exciting new paradigm for computing and learning, and demonstrate it in the lab.

We offer a PhD - position that is focused on the theoretical understanding of networks of these bistable components. The project will involve analytical and computational modelling, as well as supporting the design of experiments to be carried out by the two PhD - students in Twente. Key questions include: How to design networks of bistable elements for targeted computational tasks, and what is the space of possible computations? How do noise and experimental details impact the design and computing power? Can we use plasticity in the physical elements to materialize adaptive computing? Can we implement material learning strategies in our networks? With this research, we aim to redefine physical computation, blurring the lines between materials and computers.

To get an idea of our work, see:

[1] Kwakernaak and van Hecke, Counting and Sequential Information Processing in Mechanical Metamaterials, PRL 130 268204 (2023)

[2] Liu, Teunisse, Korovin, Vermaire, Jin, Bense and van Hecke, Controlled Pathways and Sequential Information Processing in Serially Coupled Mechanical Hysterons, PNAS 121, e2308414121 (2024).

[3] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond Matt Phys 14, 417 (2023)

[4] Dillavou, Beyer, Stern, Liu, Miskin and Durian, Machine learning without a processor: Emergent learning in a nonlinear analog network, PNAS 121, e2319718121 (2024)

[5] Kaspar, Ravoo, van der Wiel, Wegner and Pernice, The rise of intelligent matter, Nature 594, 345 (2021).

[6] Hilgenkamp and Gao, Exploring the path of the variable resistance, Science 373, 854 (2021).

[7] Zolfagharinejad, Büchel, Cassola, Kinge, Syed, Sebastian, van der Wiel, In-Materia Speech Recognition, arxiv.org/abs/2410.10434 (2024).

Qualifications
We seek candidates with a strong background in physics, electrical\mechanical engineering, materials science, or computer science with an interest in complex materials for computing and learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
The Mechanical Metamaterials group is led by Martin van Hecke, and focusses on emergent memory effects and computation in (meta)materials, with a recent focus on the physics of interacting bistable elements. The Learning Machines group is a relatively new group at AMOLF, led by Menachem (Nachi) Stern, and focuses on the development of fundamental understanding and theories regarding learning, from a physical perspective, under real world constraints.
Our group members work closely together with extensive support from us and AMOLF resources in all aspects of design, realization, and interpretation of computational models of mechanical metamaterials and physical learning systems. We have a strong focus on stimulating development of students in all professional aspects, as well as collaborations with other researchers at AMOLF and beyond. Moreover, we work closely together with international groups and companies. For more information, see https://amolf.nl/research-groups/learning-machines

Working conditions

• The working atmosphere at the institute is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
• The position is intended as full-time (40 hours / week, 12 months / year) appointment in the service of the Netherlands Foundation of Scientific Research Institutes (NWO-I) for the duration of four years
• The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
• After successful completion of the PhD research a PhD degree will be granted at a Dutch University.
• Several courses are offered, specially developed for PhD-students.
• AMOLF assists any new foreign PhD-student with housing and visa applications and compensates their transport costs and furnishing expenses.

More information?
For further information about the position, please contact:

Prof. Dr. Martin van Hecke
E-mail: M.v.Hecke@amolf.nl

Dr. Menachem Stern
E-mail: stern@amolf.nl

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

PhD-student: Computing and Learning with Material Bits

Work Activities
We are seeking a motivated PhD - student to join our team working on the theory of computing and learning in physical systems, as part of a joint theoretical/experimental program on Smart Materials for Information Processing.

With increasing demands on computing and its accompanying energy consumption, there is a pressing need for alternatives to conventional computing hardware. In this project you will investigate and develop novel design and learning strategies for computing based on networks of bistable physical elements. This work is based on recent breakthroughs in our groups. The Van Hecke group has developed techniques for in-materia computing using interacting material bits named hysterons1,2, and the Stern Group has introduced strategies for self-learning materials inspired by ideas from machine learning and neuroscience3,4. Here we aim to join these ideas, in the context of networks of multistable electronic components as developed by experimental colleagues at Twente University5-7. This is a highly ambitious program with 3 PhD - positions (one at AMOLF, two at Twente), in which we aim to establish an exciting new paradigm for computing and learning, and demonstrate it in the lab.

We are seeking a motivated PhD - student to join our team working on the theory of computing and learning in physical systems, as part of a joint theoretical/experimental program on Smart Materials for Information Processing.

With increasing demands on computing and its accompanying energy consumption, there is a pressing need for alternatives to conventional computing hardware. In this project you will investigate and develop novel design and learning strategies for computing based on networks of bistable physical elements. This work is based on recent breakthroughs in our groups. The Van Hecke group has developed techniques for in-materia computing using interacting material bits named hysterons1,2, and the Stern Group has introduced strategies for self-learning materials inspired by ideas from machine learning and neuroscience3,4. Here we aim to join these ideas, in the context of networks of multistable electronic components as developed by experimental colleagues at Twente University5-7. This is a highly ambitious program with 3 PhD - positions (one at AMOLF, two at Twente), in which we aim to establish an exciting new paradigm for computing and learning, and demonstrate it in the lab.

We offer a PhD - position that is focused on the theoretical understanding of networks of these bistable components. The project will involve analytical and computational modelling, as well as supporting the design of experiments to be carried out by the two PhD - students in Twente. Key questions include: How to design networks of bistable elements for targeted computational tasks, and what is the space of possible computations? How do noise and experimental details impact the design and computing power? Can we use plasticity in the physical elements to materialize adaptive computing? Can we implement material learning strategies in our networks? With this research, we aim to redefine physical computation, blurring the lines between materials and computers.

To get an idea of our work, see:

[1] Kwakernaak and van Hecke, Counting and Sequential Information Processing in Mechanical Metamaterials, PRL 130 268204 (2023)

[2] Liu, Teunisse, Korovin, Vermaire, Jin, Bense and van Hecke, Controlled Pathways and Sequential Information Processing in Serially Coupled Mechanical Hysterons, PNAS 121, e2308414121 (2024).

[3] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond Matt Phys 14, 417 (2023)

[4] Dillavou, Beyer, Stern, Liu, Miskin and Durian, Machine learning without a processor: Emergent learning in a nonlinear analog network, PNAS 121, e2319718121 (2024)

[5] Kaspar, Ravoo, van der Wiel, Wegner and Pernice, The rise of intelligent matter, Nature 594, 345 (2021).

[6] Hilgenkamp and Gao, Exploring the path of the variable resistance, Science 373, 854 (2021).

[7] Zolfagharinejad, Büchel, Cassola, Kinge, Syed, Sebastian, van der Wiel, In-Materia Speech Recognition, arxiv.org/abs/2410.10434 (2024).

Qualifications
We seek candidates with a strong background in physics, electrical\mechanical engineering, materials science, or computer science with an interest in complex materials for computing and learning. Excellent candidates with training in any area of science or engineering will be considered. PhD candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and welcome applicants with any background.

Work environment
The Mechanical Metamaterials group is led by Martin van Hecke, and focusses on emergent memory effects and computation in (meta)materials, with a recent focus on the physics of interacting bistable elements. The Learning Machines group is a relatively new group at AMOLF, led by Menachem (Nachi) Stern, and focuses on the development of fundamental understanding and theories regarding learning, from a physical perspective, under real world constraints.
Our group members work closely together with extensive support from us and AMOLF resources in all aspects of design, realization, and interpretation of computational models of mechanical metamaterials and physical learning systems. We have a strong focus on stimulating development of students in all professional aspects, as well as collaborations with other researchers at AMOLF and beyond. Moreover, we work closely together with international groups and companies. For more information, see https://amolf.nl/research-groups/learning-machines

Working conditions

• The working atmosphere at the institute is largely determined by young, enthusiastic, mostly foreign employees. Communication is informal and runs through short lines of communication.
• The position is intended as full-time (40 hours / week, 12 months / year) appointment in the service of the Netherlands Foundation of Scientific Research Institutes (NWO-I) for the duration of four years
• The starting salary is 2.968 Euro’s gross per month and a range of employment benefits.
• After successful completion of the PhD research a PhD degree will be granted at a Dutch University.
• Several courses are offered, specially developed for PhD-students.
• AMOLF assists any new foreign PhD-student with housing and visa applications and compensates their transport costs and furnishing expenses.

More information?
For further information about the position, please contact:

Prof. Dr. Martin van Hecke
E-mail: M.v.Hecke@amolf.nl

Dr. Menachem Stern
E-mail: stern@amolf.nl

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

AMOLF has won the NNV Diversity Award 2022, which is awarded every two years by the Netherlands Physical Society for demonstrating the most successful implementation of equality, diversity and inclusion (EDI).

Commercial activities in response to this ad are not appreciated.

Technisch Facilitair Medewerker

Work Activities
Als Technisch Facilitair Medewerker ben je altijd op zoek naar technisch oplossingen om het gebouw met een diversiteit aan onderzoekslaboratoria te verbeteren. Je wordt onderdeel van de technische dienst die valt onder de afdeling Facilities Service. De afdeling ondersteunt een levendige groep van onderzoekers en supportmedewerkers om met hen een optimale werkomgeving te creëren.

Het betreft een functie waarbij je, samen met het afdelingshoofd en twee technische collega’s, zorgdraagt voor het beheren, onderhouden en het projectmatig vernieuwen van de gebouwgebonden installaties. Het team bestaat daarnaast uit twee facilitair medewerkers die zorgdragen voor de kantooromgeving. Je werkt in een platte organisatie waarbij samenwerking met andere (onderzoeks)technici gestimuleerd wordt.

Je voornaamste taken zijn:

• Verrichten van organisatorische en projectmatige werkzaamheden op een multidisciplinair technisch gebied.
• Coördineren van specialistische beheer- en onderhoudswerkzaamheden aan (nieuwe) installaties.
• Selecteren en evalueren leveranciers/aannemers voor het uitvoeren van onderhouds- en renovatiewerkzaamheden.
• Inventariseren gebruikerseisen en wensen bij onderhoudsprojecten en op basis hiervan opstellen van specificaties, plan van aanpak, begroting en een projectplanning.
• Identificeren en verhelpen van storingen aan de gebouwgebonden installaties.
• Bereidheid storingsdiensten te draaien.

De onderhoudsplanning is gebaseerd op periodieke conditiemeting van de gebouwen. Er wordt hierbij nauw samengewerkt met onze koepelorganisatie Stichting NWO-I.

De eerste grote projecten die gepland staan, zijn het participeren in de aanbestedingstrajecten en het planmatig vervangen van het gebouwbeheersysteem en het toekomstbestendig maken van onze energiebehoefte.

Qualifications
De ideale kandidaat voor deze functie:

• Is bekend met specialistische beheer- en onderhoudswerkzaamheden aan complexe installaties. Denk hierbij aan Priva GBS, WKO en proceskoelinstallaties.
• Is bekend met normen en regelgeving zoals: NEN2767, NEN3140, NEN1010, ArboWet en SCIOS.
• Heeft ervaring met software voor onderhoudsplanning, zoals PLANON of Topdesk.
• Kan zelfstandig werken, toont initiatief en is een teamspeler.
• Kan overzicht over meerdere opdrachten tegelijk houden.
• Is Nederlandssprekend, vaardigheid in het Engels is een pré.
• Ervaring met energietechniek, systeemdynamica en/of meet- en regeltechniek is een pré.
• Is bereid om indien nodig aanvullende relevante opleidingen te volgen.

Het betreft een functie op HBO werk- en denkniveau, bij voorkeur HTS of hogere installatietechniek. Bij vergelijkbare aantoonbare kennis, ervaring en affiniteit met het vakgebied nodigen we je ook uit om te solliciteren.

Work environment
De afdeling ondersteunt twee onderzoeksorganisaties; AMOLF en ARCNL. Bij deze organisaties op het Amsterdam Science Park werken in totaal circa 240 onderzoekers en 80 ondersteunende medewerkers. AMOLF initieert en verricht toonaangevend fundamenteel onderzoek aan nieuwe, strategisch belangrijke complexe molecuul- en materiaalsystemen, in samenwerking met de Nederlandse universiteiten en industrie. Zie ook www.amolf.nl.

Het Advanced Research Center for Nanolithography (ARCNL) verricht fundamenteel onderzoek aan de fysica en technologie van nano-lithografie, in het bijzonder voor toepassing in de halfgeleiderindustrie. Het ARCNL is een publiek-private samenwerking tussen ASML en meerdere kennisinstellingen. Zie ook www.arcnl.nl.

Working conditions
De sfeer op het Instituut wordt in hoge mate bepaald door jonge, enthousiaste medewerkers. De communicatie is informeel en de lijnen zijn kort. Regelmatig worden er sociale activiteiten georganiseerd door de personeelsvereniging. De secundaire arbeidsvoorwaarden zijn uitstekend. Interne training en studiefaciliteiten zijn vanzelfsprekend. Inschaling, afhankelijk van relevante kennis en ervaring, in schaal 9 met een maximumsalaris van € 4.852,- bruto per maand exclusief vakantiegeld (8%) en eindejaarsuitkering (8,33%). Er is een vergoeding voor het draaien van storingsdiensten. De functie is voor 0.8-1 fte. We bieden een dienstverband van twee jaar, met de intentie een vast dienstverband aan te gaan.

More information?
For further information about the position, please contact Nik Noest (Teamleider Facilitaire Dienst): n.noest@amolf.nl

Application
You can respond to this vacancy online via the button below.

Online screening may be part of the selection.

Diversity code
AMOLF and ARCNL are highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

Commercial activities in response to this ad are not appreciated.

Senior medewerker Project Control voor minimaal 32 uur (4 dagen) per week

Work Activities
De voor jou belangrijkste taken en verantwoordelijkheden zijn:

• Het opstellen van (complexe) periodieke management- en/of projectrapportages en het bespreken hiervan met leidinggevende en hierover adviseren;
• Het adviseren van onderzoekers en management bij subsidieaanvragen en -toekenningen ten aanzien van financiële aspecten;
• Het signaleren van overbesteding/onderbesteding en projectrisico’s en het adviseren hierover aan de projectleider, het Hoofd Financiën en de Instituutsmanager;
• Het samen met de afdeling verzorgen van de projectadministratie;
• Deelnemen aan de jaarlijkse planning & control gesprekken met de projectleiders,
• Bijdragen aan het opstellen van de jaarrekening.

Qualifications
De ideale kandidaat voor deze functie beschikt over de volgende eigenschappen:

• Een HBO+ denk- en werkniveau;
• Een opleiding op bedrijfskundig of financieel-administratief gebied;
• Ervaring met Microsoft Office en ERP-software, bij voorkeur Unit4-ERP;
• Kennis van administratieve organisatie en subsidievoorwaarden;
• Cijfermatig inzicht en accuratesse;
• Een proactieve instelling.
• (Probleem-)analytisch vermogen;
• Kan zowel in teamverband als zelfstandig werken.

Work environment
AMOLF verricht fundamenteel onderzoek naar de fysica van complexe materie en creëert nieuwe functionele materialen, in samenwerking met universiteiten en industrie. Zie ook www.amolf.nl.

Het Advanced Research Center for Nanolithography (ARCNL) verricht fundamenteel onderzoek aan de fysica en technologie van nanolithografie, in het bijzonder voor toepassing in de halfgeleiderindustrie. ARCNL is een publiek-private samenwerking tussen ASML en meerdere kennisinstellingen. Zie ook www.arcnl.nl.

De afdeling, bestaande uit twee ervaren medewerkers, is nauw betrokken bij de inrichting én uitvoering van project control; dit omvat het ontwikkelen, inrichten, beheren en bewaken van de structuur en werking van projecten en de bijbehorende (financiële) processen. Project control adviseert de projectleiders over de (financiële) voortgang van het project en draagt zorg dat er voldaan wordt aan subsidie voorwaarden, procedures en relevante wet- en regelgeving.

Working conditions
De sfeer op het Instituut wordt in hoge mate bepaald door jonge, enthousiaste medewerkers. De communicatie is informeel en de lijnen zijn kort.Onze uitstekende secundaire arbeidsvoorwaarden zijn hier te raadplegen. Interne training en studiefaciliteiten zijn vanzelfsprekend. Inschaling vindt, afhankelijk van relevante kennis en ervaring, plaats in NWO-I CAO schaal 9/10; maximaal € 5.486 bruto per maand exclusief vakantiegeld (8%) en eindejaarsuitkering (8,33%). De functie is voor 0.8-1 fte. We bieden een dienstverband van twee jaar, met de intentie van aansluitend een vast dienstverband.

Voor aanstelling in deze functie is een ‘Verklaring Omtrent het Gedrag’ vereist. De aanvraagkosten worden door AMOLF vergoed.

More information?
Voor nadere inlichtingen over de inhoud van de functie kun je je wenden tot Jeroen Weijers via j.weijers@amolf.nl

Application
Lijkt deze baan iets voor jou? Reageer dan via de onderstaande knop!

Online screening kan deel uitmaken van de selectieprocedure.

Diversity code
AMOLF and ARCNL are highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.

Commercial activities in response to this ad are not appreciated.