For all positions we have selected candidates
ESR15 is re-opened. Apply now!
Eligibility and Mobility Rule
Early-Stage Researchers (ESRs) shall, at the time of recruitment by the host organization, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree;
Date of Recruitment normally means the first day of the employment of the fellow for the purposes of the project (i.e. the starting date indicated in the employment contract or equivalent direct contract).
Full-Time Equivalent Research Experience is measured from the date when a researcher obtained the degree which would formally entitle him/her to embark on a doctorate, either in the country in which the degree was obtained or in the country in which the researcher is recruited or seconded, irrespective of whether or not a doctorate is or was ever envisaged.
At the time of recruitment by the host organization, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organization for more than 12 months in the 3 years immediately prior to the reference date. Compulsory national service and/or short stays such as holidays are not taken into account. As far as international European interest organizations or international organizations are concerned, this rule does not apply to the hosting of eligible researchers. However, the appointed researcher must not have spent more than 12 months in the 3 years immediately prior to their recruitment at the host organization.
For refugees under the Geneva Convention (1951 Refugee Convention and the 1967 Protocol), the refugee procedure (i.e. before refugee status is conferred) will not be counted as ‘period of residence/activity in the country of the beneficiary’.
Eligibility and Mobility Rules are defined only at the first employment.
More details are available here.
We are using the Code of Conduct for the Recruitment of Researchers https://euraxess.ec.europa.eu/jobs/charter/code
Common requirements for all ESR
All the applicants are expected to:
- have a Master's degree in computer science, physics, chemistry, or engineering with and sincere interest in biology and the life sciences;
- have some prior expertise in one or more of the following fields: machine learning, modeling and simulation;
- be excellent in oral and written English with good presentation skills;
- possess strong interpersonal skills, excellent written and verbal communication, and the ability to work effectively both independently and in cross-functional teams;
- be a highly creative person with outstanding problem-solving ability and the willingness to undertake challenging analysis tasks in a timely fashion.
Furthermore, the following software skills are required:
- Excellent software engineering skills are essential. Programming skills in Python must be top-notch.
- Experience with relevant libraries (TensorFlow/PyTorch, the python scientific stack) is necessary.
- Good command of modern software development tools, from git to continuous integration pipelines, is an additional plus.
The successful candidate will also demonstrate a passion for driving scientific questions with a positive and problem-solving attitude and the willingness to undertake challenging analysis tasks in a timely fashion. Excellent English is required, both spoken and written, and the ability to work effectively both independently and in cross-functional teams. We also believe that you enjoy teamwork, have a collaborative nature, and will be an encouraging colleague to all.
Descriptions of individual ESRs
For each position, academic and Industrial hosts are provided in the order of employment sequences. For example, ESR1 will start in HMGU (Germany) and then continue his/her work in AstraZeneca (Sweden). Check this order with the mobility rule.
ESR15: Deep Learning for protein simulation
Computational modelling of drug-protein binding is of vital importance in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel candidates for biological targets, genetic studies, and gene technology. The recent combination of machine learning (ML) to accelerate quantum-mechanical (QM) calculations has already led to breakthroughs in our ability to obtain dynamical insights into small molecules. However, large realistic molecules remain out of reach of QM/ML approaches. Hence, this project aims at the development and validation of reliable QM/ML force fields to investigate the dynamics of drug-protein systems of pharmaceutical relevance.
The candidate will be integrated into the activities of the Theoretical Chemical Physics group lead by Prof. Alexandre Tkatchenko (www.tcpunilu.com) for the first half of the doctoral studies (18 months) while the second half will be carried out at AstraZeneca under the supervision of Dr. Ola Engkvist (Sweden, 18 months). This project will allow the candidate to interact with the scientific staff from some of the world’s top universities and pharmaceutical companies
For further information, please contact Dr. Leonardo Medrano Sandonas, at email@example.com, or Prof. Dr. Alexandre Tkatchenko, at firstname.lastname@example.org.
Deadline: December 1st, 2022
How to apply
Be sure that you satisfy eligibility and mobility rules!
- prepare your profile and provide sufficient details about your educational and work background, proofs of your education (or expected time of your MSc/diploma), your CV, and motivation letter;
- submit your application before the deadline of December 1, 2022 (the screening will start immediately; do not wait until the deadline to submit your application).
Screening procedure is as follows
- Each application will be screened by the respective supervisors from the host organizations
- Prospective candidates will be contacted by the supervisors for individual interviews and the best ones will be shortlisted
- The shortlisted candidates will be interviewed by the recruitment commission either in person or by SKYPE/Zoom
- The candidates will be informed by e-mail about the results of their applications