PhD Student in Computational Soil Mechanics

 

Applications are invited for a PhD student to be based within the Section of Geo-Engineering, to work on the development, implementation and application of a multiscale modelling tool as a numerical testing environment for geomaterials.

The first objective of this project is to develop and implement a numerical environment for studying the behavior of heterogeneous geomaterials in an existing finite element code. Based on the explicit modelling of fine-scale heterogeneities and discrete micromechanical structure, the homogenized, large-scale constitutive behavior is to be derived. This homogenized response of heterogeneous soils has to provide input for the formulation of constitutive relations.

Complementary to experimental element testing, the application of the numerical testing environment will allow efficient and rigorous studies of the effects of heterogeneity and microstructure on the (Multiphysics) behavior of soils. In combination with stochastic modelling, this approach will be used to formulate and calibrate stochastic material models. These models account for the small-scale heterogeneous nature of soils as well as for the associated uncertainties and will form the input for stochastic numerical models for the reliability-based design and assessment of geotechnical structures.

Requirements

• Applicants should possess a very good first degree in Civil Engineering, Geoscience, Mechanics of Materials or other related discipline.
• A good understanding of continuum mechanics and numerical modelling is essential, as well as an aptitude for scientific programming for the implementation of numerical methods in existing and new finite element codes.
• Communication skills are important, and applicants should have a high level of proficiency in written and spoken English. If your mother language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must submit proof of English proficiency from either TOEFL (minimum total score of 100) or IELTS (minimum total score of 7.0). Proof of English language proficiency certificates older than two years are not accepted.
• The successful candidate will be expected to cooperate with other members of the research team and external collaborators.

Conditions of employment

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Civil Engineering & Geosciences

The Department of Geoscience and Engineering resides within the Faculty of Civil Engineering and Geosciences, and encompasses 5 sections: Applied Geology; Applied Petrophysics and Geophysics; Geo-Engineering; Resource Engineering; and Reservoir Engineering. Current collaborations between Geo-Engineering and the wider Faculty include the Section of Offshore Engineering, and the Departments of Structural Engineering, Hydraulic Engineering, and Geoscience and Remote Sensing.

The Section of Geo-Engineering has 12 full-time and 6 part-time academic staff, and ~40 PhD and Post-Doctoral researchers. Areas of expertise include soil mechanics, dykes and embankments, foundation engineering, underground space technology, engineering geology, and geo-environmental engineering. There are extensive experimental laboratory facilities, including large-scale soil-structure interaction testing facilities and a geotechnical centrifuge, as well as excellent computing facilities including access to national High Performance Computing networks. 

Additional information

For more information about the position and for informal discussion please contact Dr. Bram van den Eijnden, +31 (0) 15 278 7443, a.p.vandeneijnden@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply before 21 June 2021 via the application button and upload:

• a detailed CV
• proof of English language proficiency
• abstract of your MSc thesis (1 page)
• the names and contact details of 2 referees
• along with a letter of application

You can apply online. We will not process applications sent by email and/or post.

A pre-Employment screening can be part of the selection procedure.

Acquisition in response to this vacancy is not appreciated.

FACULTY/DEPARTMENT

Faculty of Civil Engineering and Geosciences

JOB TYPE

PhD

SCIENTIFIC FIELD

Engineering

HOURS PER WEEK

38-40

SALARY

€ 2.395,00 - € 3.061,00

DESIRED LEVEL OF EDUCATION

University graduate

VACANCY NUMBER

TUD01154

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Postdoc Smart structures design with machine learning

 

Challenge: Designing large-scale smart structures with stimuli-induced shape change

Change: Use new machine learning techniques to accelerate the design process

Impact: Novel applications

Job description

Smart materials have been widely successful in structure programming and stimuli-induced shape change with applications ranging from sustainable transportation to deep space exploration. However, the process of developing large-scale smart structures with tailored mechanical response has traditionally followed a forward design paradigm: computationally or experimentally testing a wide range of possible structures results in an effective structure- to-property map. Capitalizing on this strategy, trial-and-error or classical design optimization methods are unfortunately expensive, sensitive to the initial design guess, and yield only a sub-optimal design. A beneficial alternative is the on-demand inverse design of optimal structures, wherein an appropriate design is identified directly which achieves a targeted property (e.g., morphed shape).  To this end, as the technologies for data-efficient machine learning (ML) become more mature, it is time to merge the benefits of smart materials and ML-accelerated design for application to large-scale structures.

This project will focus on the development of a ML-based inverse design framework for origami-inspired large-scale adaptive structures with integrated shape memory alloy based joints. Origami constructions will be leveraged for reduction of the design space, improved design interpretability, and data-efficiency of the ML-accelerated inverse design task. Potential immediate applications include inverse-designed morphing turbine blades, self-deployable wind and solar sails, multi-stiffness floating structures, adaptive cranes, reconfigurable grabs and silos, and many more.

The project is collaborative and inter-disciplinary in nature and will be jointly supervised by Dr. Jovana Jovanova (Assistant Professor, Maritime and Transport Technology) and Dr. Sid Kumar (Assistant Professor, Materials Science and Engineering) with expertise in smart structures and ML-based design techniques, respectively.

Requirements

For this position you should have the following:

• PhD in mechanical engineering, mechanical design, material science, applied mechanics or related areas,
• Good publication track-record,
• Good communication and writing skills in English,
• Desirable: experience with smart materials such as shape memory alloys,
• Desirable: proficiency in machine learning and data-driven methods.

Conditions of employment

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (€ 3.491- € 4.402). The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. An International Children's Centre offers childcare and there is an international primary school.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Mechanical, Maritime and Materials Engineering

The Faculty of 3mE carries out pioneering research, leading to new fundamental insights and challenging applications in the field of mechanical engineering. From large-scale energy storage, medical instruments, control technology and robotics to smart materials, nanoscale structures and autonomous ships. The foundations and results of this research are reflected in outstanding, contemporary education, inspiring students and PhD candidates to become socially engaged and responsible engineers and scientists. The faculty of 3mE is a dynamic and innovative faculty with an international scope and high-tech lab facilities. Research and education focus on the design, manufacture, application and modification of products, materials, processes and mechanical devices, contributing to the development and growth of a sustainable society, as well as prosperity and welfare.

Click here to go to the website of the Faculty of Mechanical, Maritime and Materials Engineering. Do you want to experience working at our faculty? This video will introduce you to some of our researchers and their work.

Additional information

For more information about this vacancy, please contact Jovana Jovanova, Assistant Professor, email: J.Jovanova@tudelft.nl, or Dr. Sid Kumar, Assistant Professor, email: Sid.Kumar@tudelft.nl.

For information about the selection procedure, please contact Nathalie van Benthum, HR advisor, email: application-3mE@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply by 30 June via the application button and upload;

• a letter of motivation explaining why you are the right candidate for this project,
• a detailed CV (including academic record, names and contact addresses of two or three referees),
• list of publications.

Virtual interviews will be conducted for shortlisted candidates. We do not require reference letters at this stage, however, the references maybe contacted before the candidate is hired.

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Acquisition in response to this vacancy is not appreciated.

FACULTY/DEPARTMENT

Faculty of Mechanical, Maritime and Materials Engineering

JOB TYPE

Postdoc Positions

SCIENTIFIC FIELD

Engineering

HOURS PER WEEK

38

SALARY

see vacancy text

DESIRED LEVEL OF EDUCATION

Doctorate

VACANCY NUMBER

TUD00824

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PhD in "Optimization methods in extremal geometry"

 

Optimization techniques like linear and semidefinite programming find applications in many practical fields, but more and more also within mathematics, for instance as a tool in proving theorems in combinatorics, geometry, etc.

In this project, you as a PhD student will explore the use of optimization techniques to tackle problems in extremal geometry such as the sphere-packing problem, the kissing number problem, and other related questions. Applications in combinatorics may also be considered.

As the student, you will be supervised by Dr. Fernando M. de Oliveira Filho of the optimization group at TU Delft. The project should offer you an opportunity to learn a great deal about optimization and its applications to geometry and combinatorics; there is moreover the opportunity to conduct independent research into topics of your interest. The position also offers generous funds for travelling.

Requirements

We are looking for excellent candidates with the following qualifications, knowledge, and skills:

• MSc and BSc degrees in Mathematics, Computer Science, or related fields.
• A solid background in mathematics and willingness to learn more about functional analysis, harmonic analysis, and representation theory.
• Some experience in computer programming and willingness to learn more about it.
• Excellent communication skills, self-motivation, independence, and the ability to work with others.
• Proficiency in English for effective communication, writing, and presentation.

Conditions of employment

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Additional information

For more information about this vacancy, please contact Dr. Fernando de Oliveira Filho by email: F.M.deOliveiraFilho@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply before 01-07-2021 via the application button and upload the following documents:

1. A cover letter motivating your application and a CV.
2. BSc and MSc academic transcripts (in English).
3. Name and contact information of two references; DO NOT send reference letters.

• A pre-employment screening can be part of the selection procedure.
• You can apply online. We will not process applications sent by email and/or post.
• Acquisition in response to this vacancy is not appreciated.

FACULTY/DEPARTMENT

Faculty of Electrical Engineering, Mathematics & Computer Science

JOB TYPE

PhD

SCIENTIFIC FIELD

Engineering

HOURS PER WEEK

38-40

SALARY

€ 2.395,00 - € 3.061,00

DESIRED LEVEL OF EDUCATION

University graduate

VACANCY NUMBER

TUD01157

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PhD candidate interdisciplinary biophysics to decipher protein self-assembly in neurodegenerative disease using super-resolution multimodal microscopy

 

We are looking for a highly skilled and motivated PhD candidate in interdisciplinary biophysics to decipher protein self-assembly in neurodegenerative disease using quantitative label-free and super-resolution multimodal microscopy.

Job description

Many diseases are associated with the formation of aberrant protein aggregates, yet controlled oligomerization provides advantages for biological structure and function. Among them are neurodegenerative diseases like Alzheimer’s or Huntington’s that are to date incurable and pose one of the grand challenges for society. Despite tremendous progress it remains unclear what causes neuronal toxicity. Different types of assemblies (oligomers, fibrils, amyloid-like aggregates, …) have been identified, but the underlying molecular mechanisms of formation remain elusive. Phase transitions are suggested to play a key role in protein aggregation of intrinsically disordered proteins such as Huntingtin. Still, direct evidence of these transitions in patient brains is missing. What role, if any, does liquid-liquid phase separation play in neurodegeneration? What molecular and cellular determinants influence these transitions? To answer these questions, a better definition of the structural and functional features of protein assemblies is necessary, including their material properties. Exploring different Huntington’s model systems, from in vitro to neuronal cells will provide maximal insight. You will use our imaging toolbox and other nanotechnology available in the department to tackle this challenge. You will also apply machine learning and correlation analysis to fully exploit our recently developed 3D quantitative phase imaging for disease monitoring. As an integral part of our team, you will have the opportunity to e.g., design new optics or to establish new synthetic cell model systems for neurodegenerative disease. We welcome applications from people with diverse backgrounds. Depending on your scientific profile and interests, the specific focus of the project can be adjusted.

This project is in collaboration with Hilal Lashuel (EPFL) and Aleksandra Radenovic (EPFL).

Requirements

For this interdisciplinary, and fully funded project (4 years), we are looking for an enthusiastic experimentalist trained in (bio-)physics, interdisciplinary nanoscience or similar areas with interest in neurobiology or a neurobiologist keen on advanced microscopy. Experience in neurobiology/neurodegenerative disease, quantitative microscopy and/or programming is a plus. The following skills will be necessary (and can be learned) during this project: protein biochemistry techniques, cell culture, advanced data analysis including machine learning, super-resolution and quantitative phase microscopy. We further expect the candidate to have a reliable and pro-active work style, to be communicative (in English) and interested in the broader field of Bionanoscience and thereby contributing to an open and interactive lab culture.

The qualified candidate will benefit from working in a growing multidisciplinary group (tudelft.nl/grussmayerlab) in a highly collaborative environment (https://www.tudelft.nl/en/faculty-of-applied-sciences/about-faculty/departments/bionanoscience).

Conditions of employment

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Applied Sciences

With more than 1,000 employees, including 135 pioneering principal investigators, as well as a population of about 3,400 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we train students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers and science communicators.

Click here to go to the website of the Faculty of Applied Sciences.

Additional information

For more information about this vacancy, please contact Kristin Grußmayer, assistant professor at the Department of Bionanoscience, email: K.S.Grussmayer@tudelft.nl

For information about the selection procedure, please contact Kristin Grußmayer, assistant professor at the Department of Bionanoscience, email: K.S.Grussmayer@tudelft.nl.

 

Application procedure

Are you interested in this vacancy? Please apply via the application button and upload:

• Motivation letter
• CV
• Names and email addresses of two or three references

Pre-inquiries may help significantly to discuss the suitability of a candidature and project to this call.  Those who are short-listed will be invited for an on-line interview.

• A pre-employment screening can be part of the selection procedure.
• Applying for an exemption for specific research and educational areas is an obligatory part of the selection procedure for this vacancy. This exemption must be obtained from the Ministry of Education, Culture and Science (OCW) before an employment contract is agreed upon. Click here for more information.
• You can apply online. We will not process applications sent by email and/or post.
• Acquisition in response to this vacancy is not appreciated.

The position will be open until 1st September or until a suitable candidate was found.

FACULTY/DEPARTMENT

Faculty of Applied Sciences

JOB TYPE

PhD

SCIENTIFIC FIELD

Natural sciences

HOURS PER WEEK

38-40

SALARY

€ 2.395,00 - € 3.061,00

DESIRED LEVEL OF EDUCATION

University graduate

VACANCY NUMBER

TUD00944

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PhD student position in Digital Health for Supporting Acute Incidents

 

The Biomedical signals and systems research group at the division of Signal processing and Biomedical engineering at the Department of Electrical Engineering is recruiting a qualified candidate for a PhD student position. We are an internationally renowned research group, focusing on research in the fields of Biomedical Engineering and Digital Health. This doctoral position is funded by the Kamprad Family Foundation (https://familjenkampradsstiftelse.se/in-english/) and is part of a strategic investment to develop and expand the Digital Health research and innovation activities at our department.

In this role you will join a research group that provides a stimulating, pleasant and flexible work environment for developing research and teaching, with a network reaching companies and health care representatives with special interest in Digital Health.

Background
The society is in the beginning of a large transformation of healthcare where more and more care, acute and chronic, will be provided in individuals' homes - supported by mobile care teams and Digital Health in many facets. Another strong trend is precision health, where the goal is to tailor care and treatments to each individual at every moment utilizing as much available data and information as possible - no matter their source.

The department and the research group
At the department of Electrical Engineering we value all our co-workers and we know that a variety of personalities and experiences makes the most creative workplaces. We therefore encourage applicants with any genders, backgrounds and abilities. Our overall ambition is to contribute to a sustainable future. We aim to create a positive impact on the development of society, both environmentally, socially and economically. Research and education are performed in the areas of Communication and Antenna systems , Systems and Control, Computer vision, Signal processing, Biomedical engineering and Electric Power Engineering. Our knowledge is of use everywhere where there is advanced technology with integrated electronics, no matter if it involves electricity, electrical signals, optical signals or microwaves. The department is a dynamic and international work environment with about 200 employees from more than 20 countries. We collaborate closely with both national and international academia, industry and medical researchers.

In our Digital Health group, we focus on sensor and data fusion in combination with clinical decision support tools using e.g. Artificial Intelligence (AI) to support informed clinical decisions and the transformation of healthcare. This advertised position will focus on care chains connecting home monitoring and acute incident detection with optimized prehospital care support, and more specifically fall incidents - a huge public health problem.

One focus area for the Digital Health research is Acute Support, Assessment and Prioritizing (ASAP), a concept for supporting acute incidents within remote/home care. One application for ASAP is prevention and supporting management of fall incidents in the home, which is a major problem afflicting tens of thousands of patients each year only in Sweden, striking patients with serious injures such as hip fractures and traumatic brain injury (TBI). A project has been created connected to ASAP for research and innovation to decrease the number of deaths and injuries due to falls in the home, named Autumn Leaves.

Project description
Health care is changing, and more care is being shifted towards home. One result is that medical devices and other equipment from different suppliers are placed in the home and generate individual-related information such as vital data, images, etc. Typical of today's applications, such as Chronic Obstructive Pulmonary Disease (COPD) and heart failure, is that changes occur over relatively long periods of time - days/weeks. Therefore, procedures, processes and technical solutions are not designed to handle acute incidents where rapid response is crucial. At the same time, the possibility of detecting emergency conditions such as a fall with equipment being present in the home, and thus the possibility of acting quickly, increases. A prerequisite is that alarms and individual-related information from different suppliers and sources are provided to the prioritization and assessment process in a standardized way. This forms the foundation of the Autumn Leaves project, which gathers several important actors and companies that together have the possibility to develop a new concept to provide clinical benefits. Autumn Leaves will establish a system innovation model where quick access to individual information from sources like sensors in the home, patient record, social care, etc., together and with various decision support reduces time delays and increases the precision of prehospital care processes generated from emergency conditions in the home.

The project focus on falls, as this is a major and growing societal problem, and at the same time an application that clearly highlights the challenges and opportunities. Other conditions may include arrhythmias, cardiac arrest, epilepsy or diabetes. The core team is the multidisciplinary network that exists in prehospital research, development and innovation in Region Västra Götaland, reinforced by several companies and the City of Gothenburg. The project goal is to design and test a prototype ready for clinical testing.

For Autumn Leaves to become successful it all starts with effectively detecting a fall from a a multitude of sensors. The PhD student's research will involve sensor and data fusion utilization in health care systems for supporting clinical care processes, informed decision making and personalized healthcare. Methods will include the use of signal processing, sensor and data fusion, as well as AI/Machine Learning (ML) to develop and test a method for fall detection that uses various data sources as input, for example fall sensors mounted on the user, such as a smartwatch or other device worn on the wrist, and non-contact techniques, such as radar technology.

Main responsibilities
In this PhD student position you will play an important role in developing an ASAP/Autumn Leaves digital platform. Your research area will cover topics like multiple sensor information fusion, signal processing and interpretation utilizing AI/ML.
Specifically, you will contribute to the development of ASAP/Autumn Leaves through the following three activities:

1) Lay the theoretical foundation for the generic ASAP platform, i.e. define, evaluate and design how different sensors should work together.
2) Be involved in the hardware and software development for the ASAP platform.
3) Scientific dissemination via journal articles and conference publications.

Besides research, the position generally also includes teaching on Chalmers' undergraduate and master level corresponding to about 20 per cent of working hours. Chalmers started a new Master of Science in Biomedical Engineering programme 2020, and has a master programme in Biomedical Engineering since around 2007.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

Qualifications
To qualify for this position, you should have a master's level degree corresponding to at least 240 higher education credits in Engineering. You also need to have:

-Experience in signal processing
-Programming skills
-Interest in the above areas.

Experience from Biomedical Engineering/Digital Health is meritorious, as well as proficiency in theory and practice of sensor and data fusion, signal processing and AI/ML.

Good verbal and written communication skills in both Swedish and English are required, and good interpersonal skills are needed. If Swedish is not your native language, you will need to be able to develop Swedish skills for facilitating project communication with potential users. Chalmers offers Swedish courses.

Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.

We offer
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg. 

At Chalmers, we seek to establish a good work/life balance. We want to provide you with the means to pick the best path possible in your pursuit of making a difference. Our ambitions in this area are reflected in the generous annual leave agreement, but also in many other areas, such as Chalmers' favourable arrangements for you as a parent. As an employer Chalmers actively strives towards providing equal opportunities for any gender.

Read more about working at Chalmers and our benefits for employees.

Application procedure
The application should be marked with Ref 20210241 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities)
• Describe your future goals and future research focus

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.

Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

Application deadline: 16 June, 2021

For questions, please contact:
Associate Professor Stefan Candefjord, Signal Processing and Biomedical Engineering (SPBME), stefan.candefjord@chalmers.se, +46 73-382 15 37

Professor of the practice Bengt Arne Sjöqvist, SPBME, bengt.arne.sjoqvist@chalmers.se, +46 70-787 77 97

Associate Professor and Head of Unit Biomedical Signals and Systems, Sabine Reinfeldt, SPBME, sabine.reinfeldt@chalmers.se, +46 31 772 80 63

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. *** 
  

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