PhD Candidate: Active Learning of Peptide-based Materials

14 Feb 2024
Job Information

Organisation/Company

Radboud University

Research Field

Physics

Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)

Country

Netherlands

Application Deadline

17 Apr 2024 - 22:00 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

40.0

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Peptide-based materials are promising candidates for multifunctional biomaterials. However, whereas the number of possible sequences is enormous, only a few of these will yield functional materials. In this PhD project, you will develop an experimental platform for the high-throughput synthesis and analysis of supramolecular, peptide-based soft materials and connect this to machine learning to navigate the peptide sequence space, and to optimise the properties of promising candidates.

In this project, you will use state-of-the-art peptide synthesizers and high-throughput spectroscopic analysis methods to characterise self-assembling peptides. By automating the data analysis, you will ensure standardised processing of your results. In collaboration with machine-learning experts, you will then use your results to predict new peptide-based materials and validate your predictions experimentally to ultimately design new supramolecular biomaterials for biomedical applications such as drug delivery or wound care.

The project is part of a new, interdisciplinary Robotlab initiative at Radboud University. To foster your interdisciplinary development, you will be allocated a personal budget to pursue projects with Robotlab colleagues elsewhere in the Netherlands. You will present your work at national and international conferences and workshops and communicate your results through peer-reviewed articles. Furthermore, you will spend up to 10% of your time on teaching Bachelor’s and Master’s students. You will also be given the opportunity to further develop yourself through additional professional training.

Requirements
Specific Requirements

• You are about to graduate or have recently graduated with a Master's degree in chemistry, chemical engineering, molecular life sciences or a similar degree, and you have a particular interest in complex molecular systems and understanding them from both experimental and computational angles.
• You have experience in physical organic chemistry, supramolecular chemistry or systems chemistry, specifically peptide chemistry/solid-phase peptide synthesis, and analysis of peptide-based materials with spectroscopy and/or scattering techniques.
• Ideally, you have programming experience (preferably in Python) or are eager to learn programming skills. Experience or affinity with machine learning or computational statistics is a plus.
• You know how to take the lead in your project, but you are also happy to support others in their work.
• You flourish in a team-centred, multicultural and international environment and you can communicate your work clearly to a wide scientific audience.
• You are fully proficient in English.

Additional Information
Benefits

• It concerns an employment for 1.0 FTE.
• The gross starting salary amounts to €2,770 per month based on a 38-hour working week, and will increase to €3,539 in the fourth year (salary scale P).
• You will receive 8% holiday allowance and 8.3% end-of-year bonus.
• You will be employed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years (4 year contract).
• You will be able to use our Dual Career and Family Care Services . Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
• Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions . You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

Selection process

You can apply until 17 April 2024, exclusively using the button below. Kindly address your application to Mathijs Mabesoone. Please fill in the application form and attach the following documents:

• A letter of motivation.
• Your CV.

The first round of interviews will take place on Wednesday 01 May. The second round of interviews will take place on Wednesday 08 May. You would preferably begin employment as soon as possible.

We can imagine you're curious about our application procedure . It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information .

Additional comments

For questions about the position, please contact Mathijs Mabesoone, Group Leader at 06 29 64 63 81 or [email protected] .

Website for additional job details

https://www.academictransfer.com/337764/

Work Location(s)

Number of offers available

1

Company/Institute

Radboud University

Country

Netherlands

City

Nijmegen

Postal Code

6525 XZ

Street

Houtlaan 4

Geofield

Where to apply

Website

https://www.academictransfer.com/en/337764/phd-candidate-active-learning-of-pep…

Contact

City

Nijmegen

Website

http://www.ru.nl/

Street

Houtlaan 4

Postal Code

6525 XZ

STATUS: EXPIRED