PhD position on Tumor and Lymph node on chip platform for cancer studies

 

Cancer is the second cause of death worldwide and it is estimated that metastases are responsible for as many as 90% of cancer deaths. It is believed that up to 70% of metastases occurs through the lymphatic system with lymphatic vessels and lymph nodes (LN) mediating the process, while the rest of them are of hematogenous origin and occur through the blood stream. LN metastasis is an independent indicator of poor prognosis. LNs are responsible for the immune response against external threats as well as the elimination of tumor cells which are considered foreign entities. Tumor cells however, have found ways to escape the immune system and even colonize LNs, which would be considered an otherwise “hostile” environment. Initially, this is achieved through secreted signals that travel to the lymph node and prepare the field, while later cancer cells migrating and homing the LN actively suppress the local immune response. Nowadays, immune response reactivation is the basis of immunotherapy success in cancer treatment. Understanding how tumors shape the LN environment and how tumor cells metastasizing to the LNs are able to suppress the immune response locally is a breakthrough, and it will help us identify novel biomarkers, and possibly targeted therapies which could be combined with existing anticancer therapies. Studying the metastatic process in real time, and doing so for individual cancer patients in a personalized manner that would also enable parallel preclinical drug testing of multiple drugs and combinations, is not possible with current methodologies.

With a number of research institutes and companies throughout Europe, we will develop and validate a tumor-lymph node-on-chip (Tumor-LN-oC) platform composed of 3D tissue models and microfluidic chips which will connect surgically removed human primary tumors and LN tissue from the same lung cancer patient. This will serve as a “biological twin” of the patient and will allow us to study the interaction of primary tumors with LNs for individual patients. This will enable the use of existing drugs, or the development of new ones that could reverse this process and inhibit tumor growth and dissemination. It will also allow the identification of novel biomarkers characterizing metastatic cells which could also be exploited therapeutically. Moreover, by employing novel imaging approaches, we will generate a spectral “finger-print” of migrating/metastasizing cells which could be used for diagnostic purposes in tumor and lymph node biopsies. The proposed technologies will provide added value to the EU cancer diagnostics and pharmaceutical industries and lower the barriers associated with the application of Organ-on-Chip technology in disease diagnosis and therapy.

The goal of this PhD position is to design a resealable microfluidic chip. The size of the chip will be compatible so as to fit under a standard microscope. The chip will consist of 2 open resealable reservoirs for placing and immobilizing the tissues and two connected culture wells, in combination with continuous recirculating flow generated by an integrated "artificial cilia"-based pump system. The microchannels connecting the two culture wells will allow direct bidirectional communication between the tumor and the LN, with a minimal flow rate mimicking the situation in the human lymphatic system. Artificial cilia have been shown to be very effective in generating flows in microfluidic chips, and are an ideal fully integrated solution for the control of recirculating flow in microfluidic networks. Fabrication of the microfluidic cartridges will be performed in two phases: the 1st generation chips will be disposable (PDMS on CaF2), will comprise materials such as PDMS for the microchannels and the chambers and CaF2 for the bottom layer. For the 2nd generation (cyclic olefin copolymer (COC) on CaF2 or glass on CaF2) the materials will be COC for the upper layer in combination with CaF2 for the bottom layer, chosen for their high chemical resistance, minimal adsorption of small hydrophobic molecules, high transparency and low autofluorescence. In the 2nd generation microfluidic chips, the upper layer will be designed to be disposable and the bottom layer to be reusable. These materials can be processed using established methods like micromachining, moulding, laser processing or chemical etching. At a later stage, both components of the microfluidic chip (upper and lower parts) can be made out of glass to reduce manufacturing costs and be compatible with industrial scale processes. The artificial cilia are made via a micro-moulding process and sub-sequent assembly in the chip.

Figure: Tumor-LN-oC integrated with artificial cilia. (a) micromoulded magnetic artificial cilia;
(b) a proposed chip design: top part: two compartments for tumor and LN samples collected from patient (COC); middle part: microfluidic circuitry for feeding and facilitating cell migration (glass), connected to top part via porous membranes; bottom: mid-IR transparent substrate (CaF2) with fixed artificial cilia patch; (c) connecting micro-channels.

Job requirements

• ambitious, self-motivated and proactive;
• have experience in working in multidisciplinary projects, preferably combining mechanical, physical and/or biological disciplines;
• knowledge and experience in microfluidics, microfabrication and/or soft lithography;
• experience in cell biology, biological imaging and sensing;
• good communication skills in written and spoken English;
• willing to contribute to education activities, such as supervising BSc and MSc projects.

Embedding

The PhD student will be supervised by Dr. Ye Wang and Prof. Jaap den Toonder from the Microsystems group. The Microsystems group is part of the Institute of Complex Molecular Systems (ICMS). The Microsystems group manages the Microfab/lab, a state-of-the-art micro fabrication facility that houses a range of micro manufacturing technologies – microfluidics technology is one of the main research pillars of the group. The candidate will also work closely with experts from Biomedical department from TU/e, and work in their state-of-the-art cell lab. The activities are part of the European research project Tumor-LN-oC, and there will be many interactions and collaborations with the other project partners.

Conditions of employment

We offer you:

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called ‘30% facility’, which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Information and application

More information

Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Ye Wang, y.wang2[at]tue.nl.

For information about terms of employment, click here or contact HRServices.Gemini[at]tue.nl

Please visit www.tue.nl/jobs to find out more about working at TU/e!

Application

We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of
  three references.
• Brief description of your MSc thesis.

We look forward to your application and will screen it as soon as we have received it.
Screening will continue until the position has been filled.

We do not respond to applications that are sent to us in a different way.

Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary please combine files.

APPLY NOW

PhD position on physics-informed machine learning for smart materials

 

Smart materials promise unprecedented advances in their exotic properties and engineering applications. Scaling traditional models for such materials faces major challenges posed by the computationally intensive first-principle models. Recent advances in hybrid approaches of physics-informed machine learning offer a great opportunity to overcome existing challenges and deliver outstanding results. Join our multidisciplinary team of scientists from Mechanical Engineering and Computer Science on this exciting journey.

Job Description

We are looking for a highly creative and motivated PhD candidate to join the Mechanics of Materials section at the Eindhoven University of Technology (TU/e). The position is in the group led by Prof. Marc G.D. Geers and co-supervised by an interdisciplinary team of scientists Ondřej Rokoš (Mechanical Engineering), Vlado Menkovski (Mathematics & Computer Science), and Martin Doškář (CTU in Prague, Department of Mechanics).

Context. Metamaterials owe their name to their unprecedented effective behavior that typically cannot be found in Nature and that often combines contradictory properties, such as being ultra-stiff & ultra-light, or auxetic behavior. These properties usually emerge from the metamaterials’ complex micro-structural morphology rather than from the properties of individual material constituents. Recent trends in metamaterial design aim at their actuation using, e.g., pneumatic or magnetic means. Metamaterials thus offer a rich design space, which can be exploited in numerous applications such as artificial muscles, medical robotics, bio-implants, soft robotics, or self-folding systems.

Objective. The objective of this project is to develop Machine Learning based solutions for the design and optimal control of engineering-scale devices, manufactured from advanced/smart active metamaterials. Optimal control of such systems with many degrees of freedom necessitates real-time yet high-accuracy multiscale simulations to predict mechanical behavior relevant at the engineering scale, hierarchically emerging from the underlying microstructure.

Development of such materials usually relies on computationally intensive first-principle microstructural models, which need to be parameterized by typical microstructural features such as varying thermo-mechanical properties of the microstructural constituents, or coupling with external fields. This results in prohibitive computational complexity that limits the possibility to scale the development of smart materials to a broader range.

Machine learning technology, such as deep neural networks, has enabled major advancements in various fields, especially in high-dimensional setting. These methods usually deliver black-box models that require large amount of supervised data and do not efficiently benefit from the existing domain knowledge. Recent advances in incorporating physical knowledge, such as physical laws in Deep Learning Models, open a promising avenue for utilizing the rich domain knowledge available in Materials Science for development of smart materials.

In this multidisciplinary project we aim to advance the state of the art of both the fields of Materials Science and Machine Learning by developing new materials and methods for efficiently incorporating domain knowledge into Machine Learning models.

Implementation. To achieve this objective, the PhD project is planned to cover several aspects of multi-scale modeling of advanced metamaterials. (i) To alleviate the limitations of the computationally intensive first-principle microstructural models, reliable forward surrogates for the computation of the effective properties need to be constructed. (ii) To cover a large design space, these surrogates need to be parameterized by typical microstructural features. (iii) Their inversion will allow for efficient search of optimal microstructures with target engineering properties. (iv) Machine learning tools will be used to discover non-standard equations governing the resulting effective systems.

Exposition. During the execution phase of this project, you will be exposed to, gain understanding, and deepen your knowledge in concepts such as advanced machine learning tools (PyTorch, TensorFlow), neural networks, variational encoders, advanced first-principle nonlinear solid mechanics & multiphysics modeling, multiscale computational homogenization, finite elements, or optimization/topology optimization techniques.

Section Embedding. The research will be embedded within the section Mechanics of Materials (www.tue.nl/mechmat), whose activities concentrate on the fundamental understanding of various macroscopic problems in materials processing and forming, emerging from the physics and the mechanics of the underlying material microstructure. The main challenge is the accurate prediction of mechanical properties of materials with complex micro-structures, with a direct focus on industrial needs. The thorough understanding and modeling of ‘unit’ processes that can be identified in the complex evolving microstructure is thereby a key issue. The group has a unique research infrastructure, both from an experimental and computational perspective. The Multi-Scale Lab allows for quantitative in-situ microscopic measurements during deformation and mechanical characterization, and it constitutes the main source for all experimental research on various mechanical aspects of materials within the range of 10-9–10-2 m. In terms of computer facilities, several multi-processor-multi-core computer clusters are available, as well as a broad spectrum of in-house and commercial software.

Job requirements

Highly talented and enthusiastic candidates with excellent analytical skills and excellent grades are encouraged to apply. An MSc degree in Mathematics, Applied Mathematics, Computer Science, Mechanical Engineering, Physics, Materials Science, or a related discipline is required, as well as a strong background in computational methods. In particular, students with a specialization in machine learning, neural networks, micro-mechanics & multi-scale modelling, and finite element techniques are encouraged to apply. The ideal candidate has excellent scientific skills with a reserach-oriented attitude, outstanding verbal and written communication skills, and is fluent in spoken and written English.

Conditions of employment

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called ‘30% facility’, which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Information and application

More information

Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Ondřej Rokoš, o.rokos[at]tue.nl.

For information about terms of employment, please click here or contact HRadviceME[at]tue.nl.

Please visit www.tue.nl/jobs to find out more about working at TU/e!

Application

We invite you to submit a complete application by using the ‘apply now’ button on this page.
The application should include:

• A cover letter in which you describe your motivation and qualification for this position.
• Curriculum vitae, including a list of your publications and the contact information of
  three references.
• A brief summary of your MSc thesis, highlighting your main contribution.
• Transcripts of your BSc and MSc degrees (with grades).

Note that we do not respond to applications that are sent to us in a different way. Both national and international applications to this advertisement are appreciated.

We are looking forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled. Promising candidates will be contacted by email.

Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary please combine files.

APPLY NOW

Doc­toral stu­dent in fungal biotechnology

 

The University of Helsinki is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. We are an equal opportunity employer and offer an attractive and diverse workplace in an inspiring environment with a variety of development opportunities and benefits.

Faculty of Agriculture and Forestry invites applications for the position of

DOCTORAL STUDENT, FUNGAL BIOTECHNOLOGY

Applications are invited for a doctoral (PhD) student position that is part of the Novo Nordisk Foundation funded project MYCOFACT (The dual role of sugar transporters in plant biomass conversion by fungi to improve microbial cell factories), led by Dr. Miia Mäkelä. The doctoral student will focus on identification and functional characterization of filamentous fungal sugar transporters, by expression in the yeast Saccharomyces cerevisiae. The appointee will also participate in the supervision of undergraduate students, and the teaching duties will cover a maximum of 5% of the total working hours.

The position is filled for a fixed term starting at the earliest from September 1st 2021. The appointed doctoral student is expected to work full time to achieve a doctoral degree in four years in accordance with the degree requirements of the University of Helsinki. Part of the project will be performed in the laboratories of a collaborator in the Netherlands.

Requirements

The successful applicant will have
• A MSc degree in microbiology, microbial biotechnology or other relevant field
• Excellent communication and writing skills in English
• Ability to work both independently and as part of a research team

Previous experience with genetic engineering of yeast and/or filamentous fungi is a requirement, and experience with CRISPR genome editing, fungal physiology and regulatory mechanisms with respect to plant biomass degradation is appreciated.

Salary and benefits

The salary is based on the job requirement scheme for teaching and research staff according to the salary system of the Finnish universities. In addition, the appointee will be paid a salary component based on personal work performance. Doctoral students start from requirement level 2. In total, the starting gross salary of a doctoral student is typically about 2200-2400 EUR per month.

Occupational health care is provided for university employees. Read more about the employee benefits at the University of Helsinki: https://www.helsinki.fi/en/about-us/careers.

Application to the position

The application should include the following documents as a single pdf file in English:
• motivation letter (max. 1 page)
• CV with full contact details, education/previous degrees obtained, prior work/research experience, list of possible publications and theses with links to their online versions (if available)
• copy/copies of the diploma(s) of previous degree(s)
• contact details of at least two referees.

The appointee does not need to hold the right to study at the University of Helsinki at the beginning of the employment, but he/she must apply for the right and obtain it during the trial period. The position has a six-month trial period.

Please submit your application using the University of Helsinki Recruitment System via the Apply link. Applicants who are employees of the University of Helsinki are requested to submit their application via the SAP HR portal. The deadline for submitting the application is June 30th 2021 (23:59 EET).

Further information on the project and position may be obtained from Academy of Finland Research Fellow, docent Miia Mäkelä, miia.r.makela(at)helsinki.fi

In case you need technical support with the electronic recruitment system, please contact HR coordinator Sari Aaltonen, sari.aaltonen(at)helsinki.fi.

• Faculty of Agriculture and Forestry: https://www2.helsinki.fi/en/faculty-of-agriculture-and-forestry
• Application process to doctoral education (including demonstration of language proficiency): https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-progr...
• About doctoral schools and programmes: https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-progr...

Due date

30.06.2021 23:59 EEST

Apply for the position

PhD Position | Nuclear-Astrophysics

 

We are looking for a qualified candidate for a 3-year PhD position (with a possibility of an extension) for a nuclear-astrophysics project focusing on theory and observations of low-mass stars and their nucleosynthesis. The project is highly international and will partly be located at the Max Planck Institute for Astronomy (MPIA) [1], Heidelberg where the student will be hired and partly at Technical University [2], Darmstadt, Germany where the PhD will be granted. Dr. Camilla J. Hansen will be the main supervisor throughout the PhD. The PhD is part of the large, recently funded EU ChETEC-INFRA project [3], and spans all three disciplines of astronomy, astrophysics theory, and nuclear experimental physics.

The goal of the project is to understand how heavy elements form – a key, open question in physics. The project focuses on how heavy elements form through slow neutron-captures which can take place in evolved asymptotic giant branch stars, either as single stars or in binary systems. Hence, a central part of the project will focus on observations of such stars, theoretical modelling of stellar evolution and nucleosynthesis, and measuring the s-process indirectly in the lab. These parts will be carried out with Dr. Richard Stancliffe at Bristol University and Dr. Ann-Cecilie Larsen at University of Oslo as co-supervisors. A central part of the project will entail direct training and extended stays at both universities. A successful candidate will have ample job opportunities in all branches of nuclear astrophysics if a further career in academia should be pursued. Moreover, through the large network [3,4] of 17 countries, the project will be guaranteed international visibility as well as access to observing time, laboratory beam time, and supercomputing hours.

Requirements:

Master degree in astronomy/astrophysics or related fields (physics will be considered as well if astronomy courses have been attended) at the time of the beginning of the studies.
Experience with programming languages such as python, IDL, and the candidate must be fluent in English.
Webpage design and C++ experience is welcome but not required.

Benefits:

Remuneration for PhD students will be according to the German public sector scale TVöD  65% E 13. Social benefits are granted according to the regulations for public service.
Travel funding will be available to the student.
Starting date is loosely set in Fall 2021, and can be negotiated.
The Max Planck Society is an equal opportunity employer and strives for a diverse community of employees. Applications from historically underrepresented or disadvantaged groups are particularly encouraged. MPIA supports its employees in their search for suitable child care.

To apply, please send a single PDF file including the five components:

1. a cover letter listing the names of referees/references (3 referees);
2. personal statement of interest explaining your motivation for pursuing a Ph.D in astrophysics specialising in either or all branches of nuclear astrophysics and observational stellar astronomy (maximum of 2 pages);
3. CV (2 pages maximum);
4. list of publications (only if applicable);
5. transcripts of your grades of courses obtained during your bachelor’s and master’s degrees with a description of the grading system. 

Close attention will be paid to the personal statement of interest.  The single PDF file should be sent to hansen@mpia.de with the topic line ‘Application_324_YourName.pdf’.

Related links:

[1] https://www.mpia.de/en

[2] https://www.tu-darmstadt.de/index.en.jsp

[3] https://www.chetec-infra.eu

[4] www.chetec.eu

Deadline:

Application: July 31st (23.59 CEST) – reference letters must be sent to the same address (`Reference_324_RefereeName.pdf’) by this date for the application to be considered.

Selection: End August / early September

 

Within the framework of the Helmholtz European Partnering Project "Innovative high performance computing approaches for molecular neuromedicine”, funded last year:
https://www.helmholtz.de/en/current-topics/press-releases/article/joint-european-research-projects-get-a-boost/

We are offering a joint PhD position in cooperation with the Institute of Neuroscience and Medicine - Nuclear Chemistry (INM-5), the Institute of Neuroscience and Medicine - Computational Biomedicine (INM-9) and the Istituto Italiano di Tecnologia in Genova (IIT). The overall goal of the project is the establishment of new lines of research in HPC for molecular neurobiology and neuroactive drug design. In particular, the candidate will develop and run in vitro assays and assays in neurons derived from iPS cells to test new compounds against D2 and isocitrate dehydrogenase 1 (IDH1), which are relevant for neurodevelopmental disorders.

We are looking to recruit a

PhD Position - Molecular Neuromedicine

Your Job:

• Develop and run biochemical assays in vitro, ex vivo (brain slices) and in neurons derived from iPS cells to discover and characterize new drugs for CNS
  
• The work will be carried out in the IIT in Genova, Italy

Your Profile:

• Excellent university degree (Master) in biology, medicine, biochemistry, or any other natural science
  
• Previous experience with molecular biology and biochemistry, neuronal primary culture and iPS cells in the field of neuroscience
  
• Excellent knowledge of written and oral English
  
• Interactive person with good communication skills
  
• Used to work in international teams

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree:

• Outstanding scientific and technical infrastructure
  
• Opportunity to participate in (international) conferences and project meetings
  
• Continuous scientific mentoring by your scientific advisor
  
• Further development of your personal strengths, e.g. via a comprehensive further training programme
  
• A structured doctoral degree programme for you and your supervisors with a comprehensive further training and networking package on our doctoral researchers’ platform JuDocs https://www.fz-juelich.de/judocs
  

The position is initially for a fixed term of 3 years. Pay in line with 70 % of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60 % of a monthly salary as special payment („Christmas bonus“). Further information on doctoral degrees at Forschungszentrum Jülich including our other locations is available at: www.fz-juelich.de/gp/Careers_Docs

Place of Employment: Genova (Italy)

Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.
We also welcome applications from disabled persons.

We look forward to receiving your application until 15.07.2021 via our
Online-Recruitment-System!

Questions about the vacancy?
Get in touch with us by using our contact form.
Please note that for technical reasons we cannot accept applications via email.

 

Understanding, engineering and control over quantum phenomena of superposition and entanglement in artificially crafted nanostructures is the primary goal of the new and emerging field of Quantum Nanoscience. Quantum nanoscience activity thus directly contributes to the second quantum revolution, which pursues the visions of quantum computing, quantum communication, and quantum sensing. Our expertise in low-temperature scanning probe microscopy (LT-SPM) puts us at the centre of the current advances, to a large extent driven by the rapid progress in LT-SPM instrumentation. In the Peter Grünberg Institute - Quantum Nanoscience (PGI-3), we do not only design and construct unique LT-SPM instruments but also apply them in cutting edge experiments.

We are offering a

PhD Position - Study of spin and charge excitations in artificially created nanostructures using an ultra-low temperature SPM in high magnetic fields

Your Job:

Your primary scientific tasks will be:

• Assembly of nanostructures on atomically clean surfaces using an LT-SPM that combines scanning tunneling microscopy (STM) and atomic force microscopy (AFM) at temperatures down to 30 millikelvin and magnetic fields of up to 8 Tesla
  
• Investigation of spin and charge excitations in the assembled nanostructures using state-of-the-art SPM techniques such as scanning tunneling spectroscopy, pump-probe spectroscopy, and electron spin resonance
  

You will also be actively involved in:

• Preparation of scientific publications and presentations
  
• Exchange with national and international scientific collaborators
  
• Training and mentoring of undergraduate students

Your Profile:

• Master`s degree in physics with excellent grades
  
• Good knowledge of quantum physics
  
• Enthusiasm and courage to explore uncharted territory, develop and follow new ideas
  
• Programming skills (e.g., Python)
  
• Preferably experience in scanning probe microscopy, ultra-high vacuum, and cryogenics
  
• Ability to work both independently as well as a part of a team
  
• Fluent in written and spoken English

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree:

• A highly motivated international working environment
  
• State-of-the-art facilities at PGI-3 including millikelvin STM, high-frequency STM/AFM, four-probe STM
  
• Outstanding research and computing infrastructure of one of Europe`s largest research centers
  
• Participation in (international) conferences and project meetings
  
• Manual and analytical skills that are in high demand both in academia and in high-tech companies
  
• Continuous scientific mentoring by your scientific advisor and close cooperation with the rest of the group and institute members
  
• A structured doctoral degree programme for you and your supervisors with a comprehensive further training and networking package on our doctoral researchers` platform JuDocs https://www.fz-juelich.de/judocs
  
• Targeted services for international employees, e.g. through our International Advisory Service
  
• The position is initially for a fixed term of 3 years. Pay in line with 50% - 75% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund), and additionally 60% of a monthly salary as special payment („Christmas bonus“).
  

Further information on doctoral degrees at Forschungszentrum Jülich including our other locations is available at: www.fz-juelich.de/gp/Careers_Docs

Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.
We also welcome applications from disabled persons.

The job will be advertised until the position has been successfully filled. You should therefore submit your application as soon as possible. We look forward to receiving your application via our
Online-Recruitment-System!

Questions about the vacancy?
Get in touch with us by using our contact form.
Please note that for technical reasons we cannot accept applications via email.

 

The Institute of Neuroscience and Medicine - Computational Biomedicine (INM-9) at Forschungszentrum Jülich develops and uses computational methods going from multi-scale molecular simulations to bioinformatics and drug design to face the challenge of understanding the molecular basis of cellular (especially neuronal) signaling processes, in healthy and disease conditions. Because of the complexity of the systems under study, simulation approaches require massive parallel computing resources such as those available at the Jülich Supercomputing Center (JSC) at Forschungszentrum Jülich.

We are offering a

PhD Position - Computational Biomedicine and Drug Design

Your Job:

• Design in silico compounds which may interfere with chronic-pain related pathways and neuroinflammation by using methodologies raging from molecular simulation to computer aided drug-design, cheminformatics and machine learning
  
• Implementation of structural Bioinformatics approaches
  
• Molecular simulation of selected targets
  
• Virtual screening and identification of potential binding entity
  
• Development and application of Chemoinformatic/Machine learning-based analyses
  
• Free-energy calculations

Your Profile:

• Excellent university degree (Master) in either biophysics, chemistry, pharmaceutical chemistry, or computer science
  
• Experience with UNIX-like operating systems
  
• Mathematical and programming skills (R, Python, Keras,Tensorflow)
  
• Ideal prior knowledge on pathway/Systems biology or MD simulations
  
• Excellent knowledge of written and oral English
  
• Interactive person with good communication skills
  
• Used to work in international teams

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree:

• Outstanding scientific and technical infrastructure
  
• A highly motivated group as well as an international and interdisciplinary working
  
• Chance of participating in (international) conferences and project meetings
  
• Opportunities of being part of an international scientific community environment at one of Europe`s largest research establishments
  
• Comprehensive training courses and individual opportunities for personal and professional further development
  
• Continuous scientific mentoring by your scientific advisor
  
• A structured doctoral degree programme for you and your supervisors with a comprehensive further training and networking package on our doctoral researchers’ platform JuDocs https://www.fz-juelich.de/judocs
  
• Targeted services for international employees, e.g. through our International Advisory Service
  

The position is initially for a fixed term of 3 years. Pay in line with 70% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60 % of a monthly salary as special payment („Christmas bonus“). Further information on doctoral degrees at Forschungszentrum Jülich including our other locations is available at: www.fz-juelich.de/gp/Careers_Docs

Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations.
We also welcome applications from disabled persons.

We look forward to receiving your application until 27.06.2021 via our
Online-Recruitment-System!

Questions about the vacancy?
Get in touch with us by using our contact form.
Please note that for technical reasons we cannot accept applications via email.