PhD position Atomistic modelling of fracture

 

In the Multi-Scale Mechanics (MSM) group led by Dr Francesco Maresca, within the Computational Mechanical and Materials Engineering (CMME) unit of the Engineering and Technology institute Groningen (ENTEG) of the University of Groningen (UG), we are looking for a PhD candidate for a project on the atomistic modelling of fracture of advanced high-strength steels, with focus on liquid metal embrittlement. This project forms the theoretical/numerical part of the MUSCLES project, which involves in total 3 researchers (one at UG and two at TU Delft) and is funded by NWO (Dutch Research Council) in collaboration with the Materials Innovation Institute (M2i) and Tata Steel Europe.

Liquid Metal Embrittlement (LME) is a major obstacle to the application of the new generation advanced high strength steels (AHSS). LME consists in the loss of ductility of the steel substrate in contact with the anti-corrosion zinc based coatings, molten upon welding operations. The fundamental origin of the mechanisms controlling LME is not understood. Literature suggests that the interaction of solutes with cracks in the material, the microstructure and the local stress state can all influence the LME phenomenon, which thus appears to be an intrinsically multi-scale process.
Therefore, a novel synergistic multi-scale experimental-theoretical approach will be developed combining state-of-the-art simulation techniques (two numerical PhD students) with cutting-edge experimental testing (one Postdoc) from atomistic up to the macroscale, to reveal the necessary insight into the LME phenomenon that is required to guide the design of LME-free AHSS. The researcher at UG will investigate the nanoscale mechanisms that induce LME by a combination of ab-initio methods (Density Functional Theory), Molecular Dynamics modelling and machine-learning.

The MSM group is active in multi-scale modelling of the mechanical properties of complex metal alloys. The research involves using and developing theoretical and computational methods at the nano- (atomistic), micro- and macro-scales to address problems of high relevance for applications. The group is part of the CMME unit, which is active in various fields of research to engineer and model across scales – from complex (meta-) materials up to integrated energy technologies – to predict and optimize the performance of materials, components and systems. The group is part of ENTEG, which is one of the 12 research institutes of the Faculty of Science and Engineering. ENTEG aims at performing excellent research and teaching directed at the integration of fundamental and engineering sciences.

Qualifications

Talented, enthusiastic candidates with excellent analytical and communication skills and high grades are encouraged to apply. A MSc degree (or equivalent) in Physics, Mechanical Engineering, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and solid mechanics theory. Experience in molecular dynamics, density functional theory and solid mechanics is important, as well as a strong interest in pursuing research in mechanics of materials. Experience in fracture mechanics modelling, machine learning, micro-mechanics, FEM simulations, crystal plasticity, metallurgy, are of benefit.

Organisation

Since its foundation in 1614, the University of Groningen has enjoyed an international reputation as a dynamic and innovative centre of higher education offering high-quality teaching and research. Balanced study and career paths in a wide variety of disciplines encourage currently more than 36,000 students and researchers to develop their own individual talents. Belonging to the best research universities in Europe and the top 100 universities in the world (see our ranking: http://www.rug.nl/(...)do-we-stand/rankings), the University of Groningen is truly an international place of knowledge.

Conditions of employment

We offer you, following the Collective Labour Agreement for Dutch Universities:

• a salary of € 2,443 gross per month in the first year, up to a maximum of € 3,122 gross per month in the fourth and final year for a full-time working week
• a full-time position (1.0 FTE) for 4 years
• a holiday allowance of 8% gross annual income
• an 8.3% end-of-the-year allowance
• a position for four years; first, you will get a temporary position of one year with the option of renewal for another three years; prolongation of the contract is contingent on sufficient progress in the first year to indicate that successful completion of the PhD thesis within the contract period is to be expected. A PhD training program is part of the agreement and you will be enrolled in the Graduate School of the Faculty of Science and Engineering.

The position is immediately available

Application

Application documents (in PDF format) must contain:

1. Letter of motivation
2. Detailed curriculum vitae (including an overview of your experience with molecular dynamics, density functional theory, theoretical solid mechanics, fracture mechanics modelling, machine learning, micro-mechanics, FEM simulations, crystal plasticity, metallurgy, Matlab/Python coding, numerical analysis; also include your date of birth and profile picture)
3. The official transcripts of your BSc and MSc grades
4. List of references with full contact information (including the supervisors of your final BSc and final MSc projects).

You may apply for this position until 6 March 11.59pm / before 7 March 2022 Dutch local time by means of the electronic application form (click on "Apply" below on the advertisement on the university's website). Promising candidates will be interviewed shortly after the deadline.

We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), https://www.nvp-hrnetwerk.nl/sollicitatiecode/ and European Commission's European Code of Conduct for recruitment of researchers, https://euraxess.ec.europa.eu/jobs/charter/code

Unsolicited marketing is not appreciated.

Information

For information you can contact:

• Dr Francesco Maresca, f.maresca@rug.nl

Please do not use the e-mail address(es) above for applications.

Apply

PhD position Food Waste: Transition from Excess to Enough

 

The food system aims at providing large amounts of food anywhere, anytime, at the expense of extensive food waste. This project investigates changes in the food system to obtain a transition from having excess to having enough, specifically focusing on the demand side. The large amount of food wasted indicates that consumers have trouble predicting their consumption levels because of preference changes and unexpected events throughout the week. A mindset shift on the side of the consumer is needed from "fear of too little" to "concern about too much". We investigate how this can be accomplished and what it entails for the way households manage their food. Do you want to contribute to a transformation in food management practices and food retailing to reduce food waste?

Qualifications

The PhD candidate should have a background (MSc, research master) in marketing or a discipline related to the topic described above, such as psychology or social sciences.

Organisation

Since its foundation in 1614, the University of Groningen has enjoyed an international reputation as a dynamic and innovative center of higher education offering high-quality teaching and research. Belonging to the best research universities of Europe and joining forces with prestigious partner universities and networks, the University of Groningen is truly an international place of knowledge.

Faculty of Economics and Business
The Faculty of Economics and Business offers an inspiring study and working environment for students and employees. International accreditation enables the Faculty to assess performance against the highest international standards. It also creates an exciting environment of continuous improvement. FEB's programmes, academic staff and research do well on various excellence ranking lists.

This PhD position is funded by NWO. The project is interdisciplinary, at the interface between consumer behavior, marketing, and design. Partners in the project are the Wageningen University & Research (Marketing and Consumer Behavior Group) and Delft University of Technology (industrial design), and we collaborate with various public and private partners such as Voedingscentrum, the Foundation United Against Food Waste, Hello Fresh, and others. More information about the project can be found here https://www.marketingandconsumerbehaviour.nl/(...)om-excess-to-enough/. This offers major advantages for the PhD candidate in terms of opportunities to collect high-quality data, additional funds for travelling, and close interactions and discussions enhancing the quality and relevancy of the research projects. The project will supervised by Prof. Jenny van Doorn and prof. Koert van Ittersum and will be embedded in SOM’s research programme in Marketing.

Conditions of employment

We offer you in accordance with the Collective Labour Agreement for Dutch Universities:

• a salary of € 2,443 gross per month in the first year, up to a maximum of € 3,122 gross per month in the fourth and final year, under the condition of a positive assessment at the end of the first year
• a full-time position (1.0 FTE)
• a holiday allowance of 8% gross annual income
• an 8.3% end-of-the-year allowance
• minimum of 29 holidays and additional 12 holidays in case of full-time employment.

An assessment may be part of the procedure, consisting of psychological tests and an interview.

Starting date: as soon as possible

Application

If you are interested, you can submit your application until 9 March 11:59pm / before 10 March 2022 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website).

The application package consists of the following separate documents:

1. your cv
2. a motivation letter (1A4 max) and a short study proposal for the PhD project (2 A4 max)
3. a scan of your diploma including transcripts
4. proof of English proficiency
5. other relevant documents.

The documents 1-4 are compulsory and please note that incomplete application packages will not be taken into account.

We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), https://www.nvp-hrnetwerk.nl/sollicitatiecode/ and European Commission's European Code of Conduct for recruitment of researchers, https://euraxess.ec.europa.eu/jobs/charter/code

Unsolicited marketing is not appreciated.

Information

For information you can contact:

• SOM Research Institute (for general information), somvacancies@rug.nl
• Prof. Jenny van Doorn, j.van.doorn@rug.nl

Please do not use the e-mail address(es) above for applications.

Apply

Postdoc researcher ERC-funded NEXT – project

 

The project NEXT – Neutron-rich EXotic nuclei produced in multi-nucleon Transfer reactions recently received funding through an ERC starting grant. PI of the grant is Julia Even, Associate Professor at the University of Groningen. The project will be embedded within the Van Swinderen Institute for Particle Physics and Gravity (VSI) at the University of Groningen.

Within the project a new solenoid-based spectrometer for multi-nucleon transfer reactions coupled to a MultiReflection Time-of-Flight MassSpectrometer (MR ToF MS) will be installed at the AGOR cyclotron facility in Groningen in order to study neutron-rich heavy nuclei. AGOR is a superconducting K=600 MeV cyclotron for the acceleration of both light and heavy ions.

The aims of the project are the discovery new isotopes in the transfermium region and to study the fission half-lives of these isotopes. Furthermore, NEXT will give access to the masses of N=126 nuclei and transfermium isotopes.

For the project, we are currently looking for an enthusiastic Postdoc with an interest in technical development and building new experimental equipment as well as online experiments and data analysis. Previous experience with electromagnetic separators, ion guide techniques and/ or precision mass spectrometry will be considered as an advantage.

Qualifications

The successful candidate has interest and experience in setting up a new experiment and running beam times. Following skills will be beneficial for the position:

• PhD in experimental nuclear physics
• experience in ion guide techniques, electromagnetic separators and/or mass spectrometry
• experience in data analysis
• good interpersonal skills,
• ability to work in a team as well as independently
• good communication skills
• ability to communicate verbally and in written form in English.

Organisation

The University of Groningen has an international reputation as a dynamic and innovative center of higher education offering high-quality teaching and research. Balanced study and career paths in a wide variety of disciplines encourage the 36,000 students and researchers to develop their own individual talents. Belonging to the best research universities in Europe and joining forces with prestigious partner universities and networks, we are truly an international place of knowledge.

Conditions of employment

We offer you in accordance with the Collective Labour Agreement for Dutch Universities:

• a salary of € 3,420 (salary scale 10) gross per month in the first year, up to a maximum of € 4,490 gross per month for a full-time position
• a full-time position (38 hours per week) for 2.5 years (April 2022 to August 2024)
• a holiday allowance of 8% gross annual income
• an 8.3% end-of-the-year allowance
• minimum of 29 holidays and additional 12 holidays in case of full-time employment
• excellent secondary benefits, including a pension scheme and flexible employment conditions.

Application

Do you meet our qualification criteria? If yes, your application should include:

• cover letter
• curriculum vitae
• summary of the PhD thesis and previous projects
• contact information of at least two academic references.

You can submit your application until 28 February 11:59pm / before 1 March 2022 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website).

Candidates are expected to start Spring 2022. The positions will be open until filled by suited candidates.

We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), https://nvp-plaza.nl/download/?id=7714 and European Commission's European Code of Conduct for recruitment of researchers, https://euraxess.ec.europa.eu/jobs/charter/code

Unsolicited marketing is not appreciated.

Information

For information you can contact:

• Julia Even, j.even@rug.nl

Please do not use the e-mail address(es) above for applications.

Apply

PhD position Statistical Physics of Learning in Neural Networks

 

Applications are invited for a fully funded PhD in the area of the statistical physics based theory of neural networks. The position is part of an NWO-supported project with the title The Role of the Activation Function in Feed-forward Learning Systems (RAFFLES).
The aim of the project is to obtain a thorough theoretical understanding of learning processes in feed-forward neural networks, with emphasis on the role of the hidden unit activation functions. We will systematically investigate layered networks for regression and classification in well-defined model situations, for which we can compare different types of activation functions and training algorithms.

The PhD student will study a variety of models and learning scenarios by using (a) analytical tools from the statistical physics of disordered systems, (b) ODE-based descriptions of the learning dynamics, and (c) Monte Carlo simulations. In particular, the following fundamental questions will be addressed:

• What is the precise influence of the choice of activation functions on the performance of multilayered neural networks?
• To what extent is the training process governed by mathematical properties of the activation functions? Delayed learning due to the necessary hidden unit specialization will be in the center of interest.
• Is it possible to identify families (universality classes) of activation functions that share characteristic properties of the training process?
• Can the theoretical insights be exploited in the design of efficient network architectures and training algorithms?

Qualifications

The successful candidate should:

• hold a Master’s degree or equivalent in theoretical physics, computer science, mathematics, or another relevant field
• have a keen interest in the theory of machine learning and artificial neural networks
• ideally come with a background in statistical and computational physics, or with a basic knowledge and strong interest in these and related areas.

Organisation

Founded in 1614, the University of Groningen enjoys an international reputation as a dynamic and innovative institution of higher education offering high-quality teaching and research. Flexible study programmes and academic career opportunities in a wide variety of disciplines encourage the 35,000 students and researchers alike to develop their own individual talents. As one of the best research universities in Europe, the University of Groningen has joined forces with other top universities and networks worldwide to become a truly global centre of knowledge.
Within the Faculty of Science and Engineering, a 4-years PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence with the topic of the statistical physics of learning in neural networks. The candidate will become a member of the Intelligent Systems Group of the Computer Science Department and will work under the supervision of Prof. Dr. Michael Biehl.

Conditions of employment

We offer you, following the Collective Labour Agreement for Dutch Universities:

• a salary of € 2,443 gross per month in the first year, up to a maximum of € 3,122 gross per month in the fourth and final year for a full-time
working week
• a holiday allowance of 8% gross annual income and an 8.3% year-end bonus
• a full-time position (1.0 FTE).

The successful candidate will first be offered a temporary position of one year with the option of renewal for another three years. Prolongation of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the next three years is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of Science and Engineering.

Application

Applications should include:

• letter of motivation
• CV (including contact information for at least two academic references)
• transcripts from your Bachelor’s and Master’s degree.

You can submit your application until 28 February 11:59pm / before 1 March 2022 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website).

Applications received before 1 March 2022 will be given full consideration; however, the position will remain open until it is filled.

We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), http://nvp-plaza.nl/download/?id=7714 and European Commission's European Code of Conduct for recruitment of researchers, https://euraxess.ec.europa.eu/jobs/charter/code

Links to related recent publications:

https://www.sciencedirect.com/(...)ii/S0378437120308153
https://link.springer.com/(...)7/s00521-021-06035-1
https://link.springer.com/(...)978-3-030-82427-3_10

Unsolicited marketing is not appreciated.

Information

For information you can contact:

• Michael Biehl, m.biehl@rug.nl

Please do not use the e-mail address(es) above for applications.

Additional information

• Michael Biehl’s website

Apply

Postdoctoral Fellow (Droplet Microfluidics and Bioanalytical Methods)

 

The Bioanalytics Group at the Department Biosystems Science and Engineering/ ETH Zurich in Basel develops a new generation of analytical instruments and methods for cell and membrane analysis using microsystems technology.

Project background

The open postdoc project aims at the the development of a microfluidic device for high-throughput cell analysis, in particular drug screening and uptake, and related bioanalytical applications. It involves droplet microfluidics, droplet manipulation and separation methods. Droplet analysis will be done by optical methods, fluorescence spectroscopy and mass spectrometry.

Job description

• Design and development of microstructured targets for MALDI mass spectrometry
• Development of assays for multimodal analysis of cells
• Development of workflows for data acquisition and analysis
• Writing of scientific publications and grant applications
• Supervision of students`projects

Your profile

We are looking for a highly motivated candidate with a strong interest to work at the interface of biology and technology development. You should have a PhD in Microsystems Engineering, Physics, Analytical Chemistry or related fields and should have already substantial experiences in microfluidics or mass spectrometry, underlined by a strong publication record in these fields. Academic excellence, a professional work attitude, and leadership potential are expected.

We offer

We offer you an intellectually challenging position in the inspiring atmosphere of an interdisciplinary team. Further information about our group and the Department can be found on the websites www.dittrich.ethz.ch and www.bsse.ethz.ch.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Interested?

We look forward to receiving your online application with the following documents:

• A letter describing your background and motivation
• CV including publication list
• Two reference letters
• Certificates (doctoral degree, master certificate)

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Questions regarding the position should be directed to Prof. Petra S. Dittrich, email (petra.dittrich@bsse.ethz.ch) (no applications).

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Apply online now

PhD position: Pangenome-wide analysis of bovine genomes

 

The Animal Genomics group at the Institute of Agricultural Sciences at ETH Zurich investigates genomic variation within and between livestock populations. The group applies different state of the art technologies to sequence the genomes of farm animals using long and short reads, and applies bioinformatics and statistical genomics approaches to characterize trait-associated sequence variation. We offer a PhD position with a focus on the long read-based assembly and pangenome integration of multiple bovine genomes. 

Project background

Long-read sequencing facilitates the assembly of large mammalian genomes. Sophisticated approaches such as «trio-binning» enable the production of two haplotype-resolved assemblies of reference quality from a sequenced trio. International consortia such as the «Bovine Pan-Genome Consortium» aim at producing haplotype-resolved assemblies for multiple breeds. Pangenomes offer a valuable framework to compare multiple haplotype-resolved assemblies and reveal structural variation within and between breeds. This project builds upon previous projects conducted by the Animal Genomics group that led to variation-aware references, multi-assembly graphs, and most recently, the first bovine pangenome from multiple haplotype-resolved assemblies. Further research is envisaged to exploit the diversity of an increasing number of haplotype-resolved assemblies, and enable pangenome-wide association testing.

Job description

We are looking for an enthusiastic and highly-motivated candidate to work on the assembly of multiple bovine genomes using long-read sequencing. You will produce haplotype-resolved assemblies using trio-binning and integrate these new resources into multi-assembly graphs to identify structural differences between individual genomes. The structural variants will be extrapolated to a large mapping population with phenotypes for dozens of complex traits using comprehensive short-read sequencing data. Association testing will be conducted to detect trait-associated structural variation. A large amount of short- and log-read sequencing data have already been collected. Comprehensive transcriptome data are also available.

This is a fully funded fixed term position for 4 years with an anticipated start date of May 1st, 2022 (negotiable). You will join the Animal Genomics group led by Hubert Pausch.

Your profile

• Strong research interest in statistical genomics, computational biology, computational genomics, or animal genomics.
• Experience with a programming language (e.g., python, R) and basic working knowledge with high-performance computing clusters is required.
• A MSc degree in genetics, genomics, computational biology, bioinformatics, agricultural sciences, animal sciences or disciplines related to the PhD position
• Affinity to computational genomics, bioinformatics and statistics is a pre-requisite.
• The writing of scientific papers and active participation in international conferences requires good knowledge of English.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Interested?

We look forward to receiving your online application with the following documents:

• Cover/motivation letter that demonstrates your suitability for the offered position and addresses the research questions you would like to develop within the project at ETH,
• Curriculum vitae with complete academic record, copies of Bachelor and Master degrees,
• Name and contact information of two references.

Evaluation of applications will start March 15th. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Questions? Further information about the Animal Genomics group can be found on our website www.ag.ethz.ch. For further information, please contact Prof. Hubert Pausch at e-mail hubert.pausch@usys.ethz.ch (no applications).

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Apply online now

Post-Doctoral Researcher - Food Process Engineering

 

The ETH Sustainable Food Processing group uses a combination of emerging food safety approaches, innovative processing of novel proteins and sustainability assessment to target fundamental challenges in food science and society such as food security.

We are starting the recruitment for a Post-Doctoral Researcher - Food Process Engineering beginning of April 2022. The position is going to be open until a suitable candidate is found. Start date by mutual agreement with the latest start date on September 1st, 2022.

Job description

We are looking for someone who is highly motivated to teach and conduct research in innovative food process engineering topics. Several food engineering courses on thermal, electromagnetic, and mechanical food processing are going to be handled and supported. You are going to have the chance to develop independent food process engineering initiatives, preferably in collaborative projects with our international/national research and/or industry partners. 

Your profile

You should have excellent academic qualifications, very good didactic and communication skills, and a strong self-motivation. We are looking for a team player. In addition, enthusiasm and talent to engage in engineering questions, in the underlying mechanisms as well as in simulation and modelling aspects is required.

Experience in thermal, electromagnetic, and mechanical food processing is important. Furthermore, the you must have a Master’s and Dr./Ph.D. degree (or equivalent) in Food Engineering, Food Technology, Mechanical Engineering, Chemical Engineering, Bioprocessing or a closely-related area.

We offer

• Continuous training opportunities for hard and transferable skills
• Perspectives for career development in academia, entrepreneurship, and industry
• A strong team culture and diverse team composition
• A flexible working environment with home office options

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Interested?

We look forward to receiving your online application with the following documents:

• cover letter including short statement of experience and qualification
• a comprehensive CV with maximum three pages and complete publication list
• a two-page research proposal considering the above defined scope outlining current challenges backed with important literature and presenting possible innovative food processing approaches to tackle these challenges
• a two-page teaching statement considering existing ETH food process engineering courses and the above defined scope with possible innovative teaching approaches
• contact information for two academic references

Applications without a research proposal and teaching statement will not be considered. Please note that we exclusively accept applications submitted through our online application portal.  Applications via email or postal services will not be considered.

Further information about the ETH Sustainable Food Processing group can be found on our website www.sfp.ethz.ch. Questions regarding the position should be directed to Dr. Lukas Böcker (lukas.boecker@hest.ethz.ch) or Prof. Dr.-Ing. Alexander Mathys by email (alexander.mathys@hest.ethz.ch) (no applications).

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Apply online now

PhD/postdoc position in numerical and/or experimental studies of single- and multi-phase granular systems

 

Granular systems are ubiquitous in nature (e.g. rock avalanches or dunes) and of fundamental importance to industry. However, despite their widespread use and occurrence, many important phenomena, such as segregation, surface instabilities or formation and coalescence of bubbles, are poorly understood. This lack of understanding can largely be attributed to difficulties in acquiring measurements of full 3D granular systems and formulating a set of governing equations for their continuum description. Recently, we have advanced Magnetic Resonance Imaging (MRI), in collaboration with Prof. Prüssmann (D-ITET, ETH), to acquire rapid measurements of particle position and velocity. In addition, we have developed numerical models to describe the heat transfer in gas-solid systems and to model non-spherical particle systems.

Job description

The objective of the current research program is to further advance our expertise in experimental and numerical approaches to probe single- and multi-phase granular systems and to elucidate currently only poorly understood phenomena such as the stability of bubbles in granular systems, particle segregation and mixing or surface instabilities.

The position is available from March 2022 onwards.

Your profile

You are expected to have a very good MSc or PhD degree in Mechanical Engineering, Physics or related disciplines. Previous experience in numerical modelling is desirable. We are looking for highly motivated, committed, and creative individual, able to work in a team and with excellent communication skills in English, both oral and written. Working in a top-level research environment, you will have a unique opportunity to develop their research abilities.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Interested?

We look forward to receiving your online application including:

• CV,
• transcripts,
• letter of motivation,
• two recommendation letters (if available).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Questions regarding the position and recommendation letters (no applications) should be directed to Prof. Christoph Müller by email muelchri@ethz.ch.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Apply online now

PostDoc position in Data-Driven and Physics-Informed Machine Learning for Cardiac Imaging

 

The CMR group at the Institute for Biomedical Engineering develops Magnetic Resonance (MR) technology and methods to assess the cardiovascular system. We devise the next generation of diagnostic tools for quantification of blood flow, organ perfusion, metabolism and function, tissue composition, microstructure and mechanics. The group exploits principles from physics, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients.

Project background

Our research has demonstrated approaches to data- and physics-informed synthesis of medical imaging data allowing to train inference machines and classifyers based on paired ground truth and synthetic imaging data. We capitalize on our previous and current work allowing to not only acquire MR imaging data of cardiac anatomy and function but also information about cardiac micro- and mesostructures derived from diffusion tensor imaging of the heart along with all parameters determining the measurement process itself.

Job description

The position to fill concerns advanced data synthesis (both via machine learning based generative models and physics simulation) and data inference (including segmentation, classification, parameter inference and mesh fitting) based on data-driven and (bio)physics-informed machine learning principles. The project aims at training and learning using both bottom-up and top-down approaches with applications to cardiac image synthesis, reconstruction and classification. The position is embedded in our overall activities of advancing MR methodology as part of improving decision support in cardiovascular patients.

Your profile

You hold a first-class PhD degree in computer science, electrical engineering, biomedical engineering, physics or applied mathematics. You should present with expertise in advanced signal and data processing and its applications to cutting-edge imaging. Excellent programming skills (Matlab/Python, C(++)) and expertise with deep learning frameworks such as PyTorch, TensorFlow, Keras. Further, you would have extensive experience with standard supervised machine learning on image data (classification, segmentation), generative image models (VAEs, GANs, diffusion models), working in the low data regime, working with 3D data (both meshes and voxel arrays), and medical image data (DICOM, NiFTI, PAR/REC).

Ideally, you would also have experience with physic-informed neural networks, and inverse imaging problems. Lastly, previous experience with student supervision is a plus, and an innovative spirit and team player skills round off your profile.

We offer

Available resources include the full range of programmable experimental and clinical MR equipment (0.75, 1.5, 3 and 7T) fully dedicated to research, advanced medical data streaming and processing machines, as well as state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU). Long-standing and very successful cooperations with clinical partners (cardiology, radiology) offer opportunities for testing and data collection in real-world applications.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Working, teaching and research at ETH Zurich

Get connected

Interested?

We look forward to receiving your online application including:

• motivation letter
• detailed CV
• study subjects including grades and
• contact information of two referees

For further information about the position and the group please contact Prof Dr Sebastian Kozerke by e-mail: kozerke@biomed.ee.ethz.ch (no applications) or visit our websites www.cmr.ethz.ch. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Apply online now