NBE Summer jobs 2022

Professor in charge of topic: Risto Ilmoniemi
Possible supervisors: Risto Ilmoniemi, Dubravko Kicic, Jaakko Nieminen, Victor Souza
Academic contact person for further information: Dr. Jaakko Nieminen, [email protected]

Title of topic: Building coil arrays for multilocus transcranial magnetic stimulation (ConnectToBrain)

Short task description:
We are looking for highly motivated candidates to participate in designing and building a coil array for magnetic stimulation of the human brain. The coil array is a cutting-edge technology developed in our research group which allows one to engage with the neural networks of the brain by an accurate control of the stimulation location and direction.

You will work developing computer algorithms and manufacturing the coil arrays. To accomplish the proposed tasks will require a good understanding of electromagnetism, linear algebra, and/or mechanical and materials engineering.

We are an international research group, and this summer work is part of the ConnectToBrain project funded by the European Research Council (ERC). The goal of the project is to develop next-generation multilocus transcranial magnetic stimulation techniques that allow to shift the locus (site in the brain) of the stimulation electronically and the algorithms to stimulate brain networks in a feedback-controlled way. The project is conducted as a close collaboration between Aalto University, Finland, University of Chieti-Pescara, Italy, and University of Tübingen, Germany (See www.connecttobrain.eu)

Requirements: Successful studies in mechanics, physics, mathematics, or engineering (e.g., mechanical, electrical, automation, control, materials); preliminary interest to continue into doctoral studies; good proficiency in the English language, in particular in writing. Ability and willingness to learn and expand one’s skill and knowledge set.

Selection criteria: Success in previous studies; motivation and ambition level.  Possible additional qualifications and experience obtained in non-standard or informal ways.

Professor in charge of topic: Prof. Risto J. Ilmoniemi
Supervisor of the project: Dr. Tuomas Mutanen
Academic contact person for further information: Tuomas Mutanen: [email protected]

Title of topic: Constructing a standard signal-processing pipeline for analyzing transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) data

Short task description:
With transcranial magnetic stimulation (TMS), we can artificially activate an interesting cortical location in the human brain by applying brief but strong magnetic pulses to the head. By simultaneously measuring the resulting electroencephalography (EEG) responses, we can learn about basic brain functioning, such as cortical connectivity. However, despite the usefulness of TMS–EEG, the measured data are often very noisy. Over the years, our lab has created several custom in-house methods and Matlab code for preprocessing the data and cleaning out the noise signals. However, sharing those signal-processing methods with our collaborating universities requires us to construct a well-structured, clearly-written, and documented repository, which can be updated on demand. In this summer project, your task is to develop a data-analysis toolbox for TMS–EEG data in GitHub that consists of a set of cleanly-written data-analysis functions and tools that read the raw data from the EEG machines and distill the genuine brain signals underneath the noisy measurement. The goal is to share the developed toolbox with our international collaborators. The toolbox will be based on pre-existing code and methods. Over the summer, you will learn much about functional brain imaging, biophysical signal processing, and good code-development practices with appropriate version control.

Requirements: Basic understanding of linear algebra, matrix operations, and signal processing. Interest in computing and programming. Familiarity with MATLAB. Successful studies in physics, mathematics, or engineering (e.g., biomedical engineering); preliminary interest to continue into doctoral studies; good proficiency in the English language, in particular in writing. Ability and willingness to learn and expand one’s skill and knowledge set.

Selection criteria: Success in previous studies; motivation and ambition level.  Possible additional qualifications and experience obtained in non-standard or informal ways.

Supervisor of the project: Dr Mia Liljeström
Academic contact person for further information: Mia Liljeström, [email protected]

Title of topic: Development of MEG/MRI analysis pipelines for studying age-related changes in the brain

Short task description:
The human brain undergoes systematic changes over the course of the lifespan, and as a consequence, many cognitive abilities decline at old age. However, there is large variability in how well preserved different functions, such as language or memory, remain at old age, and the neural underpinnings of preserved vs decline in cognitive functioning are still poorly understood. Join us in the Multimodal Imaging of Aging group where we study how age-related changes in the brain affect language function. In our project, we make use of both structural (MRI) and functional (MEG) imaging to study aging in the brain. We are now looking for a Research Assistant with a background in biomedical engineering, computational science, bioinformatics, or a related field to preprocess and develop analysis pipelines for MEG or MRI data collected from young and older adults. An interest in neuroscience and knowledge of python are considered beneficial. We offer a versatile learning experience, combining cognitive neuroscience and brain imaging with computational modeling. The project offers topics well suitable for a Bachelor’s thesis or a special assignment.

Professor in charge of topic: Risto Ilmoniemi
Possible supervisors: Dubravko Kicic, Heikki Sinisalo
Academic contact person for further information: Heikki Sinisalo, [email protected]

Title of topic: Development and assembly of electronics for multilocus transcranial magnetic stimulation (ConnectToBrain)

Short task description:
The goal of the ConnectToBrain project is to develop next-generation multilocus transcranial magnetic stimulation techniques that allow to shift the locus (site in the brain) of the stimulation electronically and the algorithms to stimulate brain networks in a feedback-controlled way. This European Research Council (ERC) Synergy project is conducted as a close collaboration between Aalto University, Finland, University of Chieti-Pescara, Italy, and University of Tübingen, Germany (See www.connecttobrain.eu)

We are looking for motivated candidates to participate in the development and assembly of electronics for multilocus TMS. Your task is to help plan, develop and realize an advanced version of the mTMS control and power electronics. This task includes circuit board design, so familiarity with electronics and circuit design is expected. Experience with embedded development is a plus.

Requirements: Successful studies in physics, mathematics, or engineering (e.g., electrical, automation, control); preliminary interest to continue into doctoral studies; good proficiency in the English language, in particular in writing. Ability and willingness to learn and expand one’s skill and knowledge set.

Selection criteria: Success in previous studies; motivation and ambition level.  Possible additional qualifications and experience obtained in non-standard or informal ways.

Professor in charge of topic: Lauri Parkkonen
Supervisors of the project: Mia Liljeström and Lauri Parkkonen
Academic contact person for further information: Dr. Mia Liljeström ([email protected])

Title of topic: Big-data approach to functional brain imaging

Short task description:
Functional brain imaging methods hold promise for producing valuable information for the diagnostics of many brain disorders; however, the application of these methods is hampered by the lack of normative data. We have developed a database for aggregating a large number of magnetoencephalographic (MEG) and functional magnetic resonance imaging (fMRI) datasets. Now the aim is to apply machine-learning methods to derive clinically relevant biomarkers. We are looking for summer intern(s) that could contribute to this project by 1) collecting normative MEG data and/or, 2) testing machine-learning approaches on normative data acquired from healthy participants of different age groups, or 3) by devising and implementing software solutions for the database. Suitable candidates have working knowledge in Python programming and machine learning, or master the basics of database solutions. The project is well suited for doing a thesis or a special assignment.

Professor in charge of topic: Lauri Parkkonen
Supervisor of the project: Juan Avendano and Lauri Parkkonen
Academic contact person for further information: Juan Avendano, [email protected]

Title of topic: Two-person neuroscience with MEG hyperscanning

Short task description:
Magnetoencephalography (MEG) refers to the measurement of human brain activity through the magnetic field generated by electrically active neuron populations. Most research in human social neuroscience (using MEG and other techniques) has been based on experiments where participants perform tasks in isolation, as spectators in controlled environments and responding to well controlled stimuli. However, it has been argued that studying human brains in isolation cannot reveal the neural mechanisms underlying complex, dynamic, real-life social interactions, and instead, studying two or more subjects simultaneously might be needed. Hyperscanning refers to the simultaneous recording of brain signals from two or more individuals. We have implemented such a set-up involving two interconnected MEG systems. This set-up allows us to measure and examine the brain activity of interacting individuals in naturalistic settings, with the aim of extending our understanding of the brain basis of social interaction.

We are now looking for highly skilled and motivated individuals to contribute to this endeavor through the analysis of previously acquired data sets, and the collection of brain data in new experiments. The required knowledge and skills depend on the task (we will try to find something that fits your skills and interests) but good programming skills (preferably Python and/or Matlab) and signal processing are essential. Some background in complex systems could be a plus for some of the tasks.

Professor in charge of topic: Lauri Parkkonen
Supervisor(s) of the project:Lauri Parkkonen and Ivan Zubarev
Academic contact person for further information: Lauri Parkkonen, [email protected]

Title of topic: On-scalp MEG with optically-pumped magnetometers

Short task description:
Magnetoencephalography (MEG) refers to recording brain activity through the magnetic field generated by electrically active neuron populations. MEG measurements are traditionally done with superconducting sensors that must be kept few centimeters away from the scalp due to the required thermal isolation. However, recent advances in quantum optics have enabled magnetic field sensors that no longer require cooling and can thus be placed directly on the scalp, thereby increasing signal strength and spatial resolution. Employing such sensors, we have constructed a novel high-resolution MEG system for studying brain function in a new way. We are now looking for highly skilled and motivated individuals to develop this system further and to apply it to brain measurements. The project offers multiple tasks and positions: magnetic field modeling and coil design, electronics design, software development, and human brain measurements (incl. brain–computer interfacing) and the associated data analysis. The required knowledge and skills depend on the task; some Python programming skills and signal processing are essential in all of them while also good command of university math and physics are needed in the more system-related tasks.

Professor in charge of topic: Risto Ilmoniemi
Possible supervisors: Timo Roine, Olli-Pekka Kahilakoski, Victor Souza, Andrey Zhdanov
Academic contact person for further information: Dr. Timo Roine, [email protected]

Title of topic: Software for real-time EEG-controlled brain stimulation (ConnectToBrain)

Short task description:
The goal of the ConnectToBrain project is to develop next-generation multilocus transcranial magnetic stimulation (mTMS) techniques that allow to shift the locus (site in the brain) of the stimulation electronically and the algorithms to stimulate brain networks in a feedback-controlled way. This European Research Council (ERC) Synergy project is conducted as a close collaboration between Aalto University, Finland, University of Chieti-Pescara, Italy, and University of Tübingen, Germany (See: www.connecttobrain.eu)

We are looking for highly motivated candidates proficient in software development to participate in developing and designing software for real-time electroencephalography (EEG)-controlled brain stimulation. The work will be done as a part of a team and consists of one or several of the following areas, depending on the needs and the applicant’s interests: integration of the EEG equipment, user interface development (backend/frontend), integration of software components in the architecture, designing and documenting application programming interfaces, adding features to and improving existing code.

Requirements: Proficiency in Python; Experience in Git, MATLAB, C/C++, web development, and microservice architectures are considered benefits; Good communication and collaboration skills; good proficiency in the English language, in particular in writing. Ability and willingness to learn and expand one’s skill and knowledge set.

Selection criteria: Success in previous studies; motivation and ambition level.  Possible additional qualifications and experience obtained in non-standard or informal ways.

Professor in charge of topic: Iiro Jääskeläinen
Supervisor of the project and academic contact person for further information: Iiro Jääskeläinen, [email protected]

Title of topic: Cognitive Neuroscience

Short task description:
The Brain and Mind Laboratory at the Department of Neuroscience and Biomedical Engineering is calling for applications to (at least) one open summer internship position.

The selected summer workers will be employed from ~mid-May to end of August, the exact starting date to be agreed upon, and their tasks will be highly versatile, helping out in neuroimaging and behavioral data acquisition and data analyses, which gives very good learning opportunities.

We are a dynamic group primarily engaged in using naturalistic stimuli, such as movies and narratives, to study human higher cognitive functions and emotions with fMRI, MEG/EEG, and behavioral measures, including eye-movement recordings. We are especially interested in advancing understanding of social cognition, including perception of ingroup vs. outgroup members.

Given the complex nature of resulting data, our group is developing analysis methods that enhance possibilities to use naturalistic stimuli in human cognitive neuroimaging, and shares such methods with other neuroscientists globally. The workplace language of our laboratory is English due to international composition of personnel, and we are a highly multidisciplinary laboratory.

Academic contact person for further information: Jani Oksanen, [email protected]
Possible supervisors: Ivan Radevici, Benoît Behaghel, Pyry Kivisaari

Title of topic: Energy conversion devices based on iii-v compound semiconductors

Short task description:
Our group develops energy conversion technologies enabling new approaches to optical cooling, thermal energy harvesting and chemical energy conversion processes. In this internship you can contribute to our work and learn about these technologies and the related compound semiconductor physics and chemistry. The possible research topics involve a variety of topics related to the device fabrication, the properties of the individual constituents of the devices and the modeling of the devices. Some specific topics include e.g. the fabrication and characterization of conductive high reflectivity mirror structures, ion implantation doping of III-V devices and electrochemical characterization of the iii-v semiconductors.

We are most interested in candidates with studies in physics, compound semiconductor technologies, electrochemistry and/or optoelectronics and fast progress, good marks and interest to learn more about semiconductors. If you are sufficiently far in your studies or interested in a master's thesis topic, we expect to have the possibility to also continue or start the internship with a master's thesis leading towards doctoral studies. The final topic of the internship depends on the candidate(s) and can be adapted to suit his/her skills and interests. The experimental work takes place at the Micronova clean room facilities.

Professor in charge of topic: Petri Ala-Laurila
Supervisor of the project and academic contact person for further information: Aarni Seppänen, [email protected]

Title of topic: Correlating neural circuit function to behavioral performance

Short task description:
A summer intern position is immediately available in the laboratory of Professor Petri Ala-Laurila at the Department of Neuroscience and Biomedical Engineering (NBE), Aalto University School of Science.

We study neural processing mechanisms using a uniquely integrative approach, where we link photon distributions with retinal processing and visually-guided behavior. The goal is to break new frontiers by revealing fundamental principles of neural computations across brain circuits in multiple model species. We combine cutting-edge electrophysiological recording techniques with precise manipulations of retinal circuit function, deep-learning-based state-of-the-art animal tracking, mathematical modelling and quantitative behavioral measurements.

We are currently seeking to hire one highly motivated summer intern with a potential for long-term attachment to our research group. Apply now if you have a genuine interest in studying neural circuits, animal behavior and the underlying mechanisms. For details, see our paper revealing the decoding principles of visual signals at spike resolution - Neuron  2019 – and another key paper revealing the impact of behavioral strategy on visual sensitivity: Current Biology, 2020 as well as the lab’s webpage.

Professor in charge of topic: Matias Palva
Supervisors of the project: Matias Palva
Academic contact person for further information: Matias Palva, [email protected]

Title of topic: Brain dynamics, computer games, and personalized medicine

Short task description:
We are working on computer games that can be used in personalized treatment of brain disorders. We also have several lines of brain imaging studies aiming to uncover the systems-level neuronal mechanisms that underlie mental disorders including depression, anxiety, and schizophrenia as well as neurological disorders such as Alzheimer’s disease.

In this summer intern project, we are looking for a student who could contribute to the implementation and performing of machine learning (and other) data analyses to both action video game and brain imaging data. It would also be possible to participate to human brain imaging experiments for recording brain activity during gaming itself. The project will yield interesting results in both applied-sciences and basic-neuroscience-research contexts.

Suitable candidates would be proficient in Python programming and master the basics of time-series analysis and machine learning. Please also indicate if you are interested in doing B. Sc. or M. Sc. thesis as a continuation of the project or a special assignmen

Professor in charge of topic: Risto Ilmoniemi
Supervisors of the project: Koos Zevenhoven, Marko Havu
Academic contact person for further information: Risto Ilmoniemi, [email protected]

Title of topic: MEG–MRI Brain Imaging

Short task description:
The MEG-MRI Brain Imaging group (https://www.aalto.fi/en/department-of-neuroscience-and-biomedical-engineering/meg-mri-brain-imaging-group) offers two summer internship positions.

You will work on a whole-head MEG–MRI scanner prototype and its applications. The system uses an array of superconductor-based sensors for both magnetoencephalography (MEG) and magnetic resonance imaging (MRI) of the brain. This will enable localizing brain activity with unprecedented accuracy and tracking it in millisecond scale. Depending on your background and interests, your project may include, for example, electronics design, modelling, planning and conducting experiments, signal processing, machine learning, statistics, and programming.

Selection criteria: Success in previous studies; motivation and ambition level.  Possible additional qualifications and experience obtained in non-standard or informal ways.

Professor in charge of topic: Riitta Salmelin and Hanna Renvall
Supervisor of the project and academic contact person for further information: Riitta Salmelin, [email protected]; Hanna Renvall, [email protected]

Title of topic: Individual neural markers of cognitive processing

Short task description:
The Salmelin and Renvall groups (https://www.aalto.fi/department-of-neuroscience-and-biomedical-engineering/imaging-language, https://biomaglaboratory.fi ) offer 2-3 summer internship positions. Our multidisciplinary groups seek to understand how cognitive functions are represented in the human brain and how those functions, and their disorders, may be best assessed using functional and structural brain imaging (MEG/EEG, f/MRI, multimodal imaging). A particular focus area are language-related cognitive functions. Advanced computational analysis tools are essential in modelling and quantifying such representations. We are currently pushing the boundaries of research from the widely used group-level descriptions to next-generation cognitive neuroscience of individual-level predictions. Examples of summer projects include using machine learning to detect individually unique brain patterns in health and disease, influence of attention on time-locking of cortical processing to speech vs other natural sounds, machine-learning based decoding of word meanings from MEG data, and using ICA to extract shared and independent information picked up by different imaging methods such as MEG, EEG and fMRI. The student will join in an active research project, with an opportunity to learn and contribute to neuroimaging and behavioural data acquisition, data analyses, computational modelling etc. A suitable background is in cognitive neuroscience, computational science, biomedical engineering, bioinformatics, mathematics or a related field. The research environment is multilingual so a good command of English is a necessity. Basic knowledge of brain imaging methods and previous experience in scripting/programming (e.g. Python, Matlab) are considered an asset.

Professor in charge of topic: Anton Kuzyk
Academic contact person for further information: Anton Kuzyk, [email protected],Sesha Manuguri, [email protected], Jacky Loo ([email protected])

Title of topic: Advanced Plasmonics Enabled by DNA Nanotechnology

Short task description: Experimental interdisciplinary research on DNA nanotechnology, molecular self-assembly and nanoplasmonics in a multidisciplinary international environment with excellent instrumentation and facilities.

Examples of available topics:

• Stimuli responsive DNA origami-based plasmonic assemblies (preferred background: physics, biochemistry and/or biotechnology)
• Synthesis and characterization of dynamic plasmonic DNA-based hydrogels (preferred background: chemistry, soft matter physics, and/or materials science)
• Active plasmonic surfaces (preferred background: physics, chemistry)

Qualifications: An ideal candidate has a solid background and/or strong interest in applied physics, bionanotechnology and/or soft matter physics. Previous experience in molecular self-assembly and nanomicroscopy (AFM, TEM, SEM) is an advantage. The position requires excellent communication skills in written and spoken English. The specific topic will depend on the background and research interests of the successful candidate.

Further information about the group:

https://goo.gl/k9EtLx

Examples of our previous work

“Light-responsive dynamic DNA-origami-based plasmonic assemblies”

https://onlinelibrary.wiley.com/doi/10.1002/anie.202014963

 “Selective control of reconfigurable chiral plasmonic metamolecules”

http://advances.sciencemag.org/content/3/4/e1602803

“Reconfigurable 3D plasmonic metamolecules in the visible wavelength range”

https://www.nature.com/articles/nmat4031

Supervisor of the project: Staff Scientist Toni Auranen
Academic contact person for further information: Toni Auranen, [email protected]

Title of topic: Comparing and optimizing SNR in fMRI paradigms

Short task description:
Functional magnetic resonance imaging (fMRI) is a widely used neuroimaging modality to study human brain networks with simple or complex stimuli or tasks. It provides accurate mm-scale location information of the blood oxygen level dependent (BOLD) contrast with a temporal resolution in the second-scale. Recent advances in the field have brought methods, such as simultaneous multi-slice echo-planar imaging (SMS-EPI), to the reach of the vast user community. These methods improve the temporal resolution of fMRI close to 300-500 ms and even below with ultrafast methods, such as MR-encephalography (MREG). However, optimizing the signal-to-noise ratio (SNR) of the fMRI paradigm is not always trivial as the number of parameters in the scanning phase increases. The purpose of this project is to compare the effect of different parameters to the SNR of the fMRI data. The position offers a first-hand opportunity to learn and dwelve into the heart of fMRI measurements. The applicant should demonstrate good understanding of basic principles of signal processing and human neuroscience. Prior knowledge of MRI/fMRI and especially fMRI data analysis experience is considered as an advantage. Candidates should also have good command of English and possess exact and diligent learning and working abilities as the planned measurements and analyses require precision and accuracy. Students who are in their early phase of studies are also considered especially if they are already showing interest in research career/doctoral studies.

Professor in charge of topic:  Iiro Jääskeläinen
Supervisor(s) of the project: Yoni Levy 
Academic contact person for further information:  Yoni Levy, [email protected]

Title of topic:  Empathy Neuroscience

Short task description: 
A summer intern position is available at The Empathy-Building Neuro-lab, in the Department of Neuroscience and Biomedical Engineering (NBE) at Aalto University School of Science. Empathy is the ability to feel and understand each other. But it becomes difficult to experience empathy in situations of conflict, politics, immigration and even as recently seen, in times of pandemic. In such situations, our emotions and attitudes often block the ability to empathize. In our lab, we use MEG and fMRI as well as philosophical approaches (i.e., phenomenological interviews) to investigate empathy in such situations. 

The ideal candidate for this position should (1) be curious, motivated and highly interested in this topic, (2) have familiarity or proficiency in matlab or python. This combination can allow the selected candidate to have a very exciting and productive summer internship in our lab!

Professor in charge of topic: Stéphane Deny
Supervisor of the project and academic contact person for further information: Stéphane Deny, [email protected]

Title of topic: Modelling mental rotation in the visual system

Short task description:

This project consists in studying and modelling how the visual system performs mental rotation of 3D objects. The selected summer student will be employed from ~mid-May to end of August, the exact starting date to be agreed upon, and their tasks will be highly versatile, helping out in designing stimuli, collecting neuroimaging and behavioral data, performing data analysis, and developing computational models of the visual system, depending on the preferences of the student and the availability of experimental tools and collaborators. The project should be a good learning opportunity for a student interested in developing their experimental and/or modelling skills in computational neuroscience.

Field of study: Clinical neuroscience

Professor in charge of topic: Iiro Jääskeläinen

Supervisor of the project and academic contact person for further information: Juha Salmitaival, [email protected]

Title of topic: Clinical Cognitive Neuroscience

Short task description: Translational Cognitive Neuroscience Neuroscience Lab (www.aalto.fi/en/department-of-neuroscience-and-biomedical-engineering/translational-cognitive-neuroscience-lab) is seeking for applicants for 1-2 summer internship positions.

The work mainly relates to The Academy of Finland funded project ’Bringing real-life to attention research’. We have recently developed a new game of daily living (see https://drive.google.com/open?id=1-vVxs4sfrsI-8g4QrwWCbadYjsrDOB4G) that we use for studying cognitive and brain functions in children with ADHD. In some studies the participants play the game with a VR headset at the laboratory. We are also collecting home-based testing data with a web-browser version, which is not influenced by possible COVID regulations for laboratory studies. In addition to the behavioral data, we collect functional brain imaging data. Depending on the interests of the summer worker (the exact period to be agreed upon), she/he can participate to various tasks related to neuroimaging and behavioral data acquisition and data analyses. The project gives learning opportunities from modeling the complex gaming data (e.g., head movements, location data, interaction with the environment) with advanced computational methods to various technologies used in clinical cognitive neuroscience, not forgetting the practical skills related to clinical research data acquisition.

We are a multidisciplinary group of neuroscientists, game developers, medical doctors and data analysts that tackle the socially relevant questions related to 1) developing online technologies to cost-efficiently conduct medical/clinical assessments, 2) gamifying the neuropsychological/psychiatric assessments and rehabilitation to increase the engagement of the participants, 3) and most of all to help increasing number of children with attention deficits to manage the information overload of the modern society. The summer worker will be supported by a larger team consisting of senior researchers, as well as PhD and Master's students.