NBE Summer jobs 2023

Professors in charge of topic: Riitta Salmelin and Hanna Renvall
Supervisors of the project : Riitta Salmelin and Hanna Renvall
Academic contact persons for further information: Riitta Salmelin, [email protected]; Hanna Renvall, [email protected]

Title of topic 1: 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, neural processing of noisy language, 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.

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

Title of topic 2: 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 interested in biomedical engineering, computational science, bioinformatics, or a related field to preprocess and develop analysis pipelines for MEG or MRI data. 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: Lauri Parkkonen
Supervisors of the project: Mia Liljeström and Lauri Parkkonen
Academic contact person for further information: Mia Liljeström ([email protected])

Title of topic 3: 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 database solutions 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) developing the measurement protocol and collecting normative MEG data and/or, 2) performing preprocessing and testing machine-learning approaches on normative data acquired from healthy participants of different age groups. Suitable candidates have working knowledge in Python programming and machine learning and an interest in human neuroscience. The project is well suited for doing a thesis or a special assignment.

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

Title of topic 4: Interpersonal psychophysiology: MEG hyperscanning & Social biofeedback

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.

In biofeedback systems, users are presented with accessible information reflecting some aspects of their physiological signals, that can be used to learn to monitor/control their own physiological activity, or subjective states related to these signals. Biofeedback systems have been successfully employed in several clinical and recreational applications. An open question, however, is to what extend these systems could be used to help us understanding other people’s physiology, enhance our sense of connectedness, or modulate remote social interactions. We aim at developing a social biofeedback platform, and testing whether/how externalizing interpersonal physiological information from two individuals, can be used to enhance/modulate remote social interactions (i.e., when the two individuals are in different locations, only connected via a computer display/app).

We are now looking for highly skilled and motivated individuals to contribute to these endeavors through the analysis of previously acquired MEG hyperscanning data sets, the collection of brain data in new experiments, or the development of a social biofeedback platform and related 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, machine learning, game design or human-computer interfaces could be a plus for some of the tasks.

Professor in charge of topic: Lauri Parkkonen
Supervisors of the project: Lauri Parkkonen, Ivan Zubarev, Mikael Grön
Academic contact person for further information: Lauri Parkkonen, [email protected]

Title of topic 5: High-resolution brain measurements

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 centimetres 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 optically-pumped magnetometers (OPMs), we have constructed a novel high-resolution MEG system for studying human and animal brain function in a new way. We are also developing these OPM sensors further as a partner in a European research consortium.

We are now looking for highly skilled and motivated individuals to develop OPM-based MEG further and to apply it to brain measurements. The project offers multiple tasks and positions: magnetic field modelling and coil design, mechanical design, electronics design, software development, development of real-time analysis and brain–computer interfaces, measurements of human and animal brain (domestic cats and dogs) function 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 mathematics and physics are required in the more system-related tasks. Basic neuroscience and machine-learning knowledge would be useful but not mandatory in the brain measurement and analysis tasks.

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

Title of topic 6: Functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS) methods

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 contrast with a temporal resolution in the second-scale. Magnetic resonance spectroscopy (MRS) is a spectroscopic technique in the field of MR that can be used to study brain metabolism both in static and functional setting.

The purpose of this project is to study functional brain imaging methods using fMRI/MRS and specifically develop a practical MRS paradigm and test its applicability also in a functional setting. In addition, the summer intern will take part in especially fMRI and MRS measurements/analyses with an intermittent photic stimulation paradigm in another project of this call.

The applicant should demonstrate good understanding of basic principles of signal processing, neuroimaging and human neuroscience. Candidates should also have good command of English and possess exact and diligent learning and working abilities. Students who are in their early phase of studies are also considered especially if they are showing interest in research career/doctoral studies and have prior knowledge and/or experience of MRI/fMRI/MRS.

Academic contact person for further information: Veikko Jousmäki ([email protected])

Title of topic 7: Intermittent photic stimulation (IPS) studies in magnetoencephalography, functional magnetic resonance imaging, and magnetic resonance spectroscopy

Short task description:
Aalto NeuroImaging has developed Euphotic stimulator, a novel proof-of-concept for intermittent photic stimulation device for functional neuroimaging modalities, e.g., magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and magnetic resonance spectroscopy (MRS).

We are looking for a motivated summer intern to 1) participate in MEG, fMRI, and MRS recordings, 2) develop data analysis tools and pipelines for the project, and 3) document the results.

An ideal candidate should have skills in software development in Python and motivation to learn functional neuroimaging methods available at Aalto NeuroImaging.

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

Title of topic 8: 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. Empathy is essential for us as individuals and as a society. But it becomes difficult to experience empathy towards individuals from other social groups (e.g., opposing political parties, immigrants etc). In our lab, we use MEG and fMRI to investigate empathy and prejudice in such contexts. 

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

Title of topic 9: 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.

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 10: 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: Tuomas Turunen, [email protected]

Title of topic 11: Correlating neural circuit function to behavioral performance

Short task description:
A summer intern position is immediately available in the laboratory of Adjunct 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 & Current Biology 2022 - and a 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 12: Brain dynamics, video games, and personalized medicine

Short task description:
We are working on personalized digital therapeutics for brain disorders where video games are used as the media. 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 at least 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 assignment. 0-2 students will be recruited.

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

Title of topic 13: Energy conversion and optical cooling devices based on iii-v compound semiconductors

Short task description:
Our group develops solid state 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 tasks deal with 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, operation temperature optimized reflective contacts 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 in learning more about semiconductors. If you are sufficiently far in your studies or interested in a master's thesis topic, also the possibility to combine the internship with a master's thesis leading towards doctoral studies exists. 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: Anton Kuzyk
Supervisor of the project: Anton Kuzyk
Academic contact person for further information: Anton Kuzyk ([email protected])

Title of topic 14: DNA-origami based plasmonic nanostructures for photothermal applications

Short task description:
Metal nanostructures have great potential for applications in various fields, including photonics, sensing, therapeutics, diagnostics etc. Recently, our group has developed novel approach to fabrication of metal nanostructures with complex programmable shapes. We anticipate that such nanostructures can be used for highly efficient light-to-heat conversion, which is crucial for development of effective therapeutic approaches based on photothermal effects. In this summer project we aim to evaluate performance of various metal nanostructures as light-based nanoheaters. In addition, we will explore whether light-to-heat conversion can be used for controlled release of bioactive molecules. For the project we are looking for highly motivated students with aptitude for interdisciplinary experimental research and interest in DNA nanotechnology, molecular self-assembly, and plasmonics. We expect solid background and/or strong interest in applied physics, (bio)nanotechnology and/or nanophotonics. Previous experience in molecular self-assembly and nanomicroscopy (TEM, SEM) is an advantage.

As a member of the group, you will be trained in advanced methods in DNA nanotechnology (especially DNA origami), and state-of-the-art electron beam nanomicroscopy techniques (TEM, SEM). You will work on design, fabrication, and characterization of metal nanostructures with particular focus on light-to-heat conversion.

The project will last for 3-4 months and there is an option to conduct a special assignment or continue with a MSc thesis.

Further information about the group:
https://goo.gl/k9EtLx

Examples of our previous works
https://scholar.google.com/citations?user=yL5QQkwAAAAJ&hl=en

Professors in charge of topic: Anton Kuzyk & Heikki Nieminen
Academic contact persons for further information: Prof. Anton Kuzyk ([email protected], +358 50 443 0492) and Prof. Heikki Nieminen ([email protected], +358 50 3389932)

Title of topic 15: Ultrasound-enabled self-assembly of nano-scale devices

Short task description:
Self-assembly enables construction of a large variety of nano-scale functional devices having great potential in various life science applications. However, controlled ways of making such devices is challenging and a topic of wide research. Ultrasound is high frequency sound that can provide oscillatory and unidirectional forces on matter, which could open novel approaches for implementing programmable control of self-assembly. 

In this summer project we aim to study how ultrasound could be used to control molecular and colloidal self-assembly processes for fabricating nanoscale devices. We are looking for a student with chemistry, nanotech or biomedical engineering background to work on the project. The student is expected to have an aptitude for  and/or experience with multidisciplinary experimental work. The student is expected to gain skills in e.g. optimizing a custom-made ultrasound system, fabricating nanoscale devices, microscopy (optical, electron microscopy), analysis and reporting. The project will last for 3-4 months and there is an option to conduct a special assignment or continue to complete a M.Sc. thesis.

The project will be a joint effort of two research groups: Molecular Nanoengineering and Medical Ultrasonics Laboratory (MEDUSA).

For more information, please contact Prof. Anton Kuzyk ([email protected], +358 50 443 0492) and Prof. Heikki Nieminen ([email protected], +358 50 3389932).

Possible supervisors: Timo Roine, Olli-Pekka Kahilakoski
Academic contact person: Dr. Timo Roine, [email protected]

Title of topic 16: Software for real-time closed-loop 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.

Supervisors of the project: Dr. Pantelis Lioumis, Dr. Tuomas Mutanen, Dr. Victor Souza, Dr. Dubravko Kicic Academic contact person: Dr Pantelis Lioumis, [email protected]

Title of topic 17: Connecting real-time EEG to the neuronavigation and the robotic system for self-driving brain stimulations

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 excitability connectivity, but also intensions, imageries and other cognitive human abilities. A Brain-Computer Interface (BCI) is a communication link for controlling computer systems based on brain activity. Early research successes include utilizing BCI to allow a monkey by thinking either to operate a robotic arm (2008) or to play video games with a virtual joystick (2018; Elon Musk’s Neuralink). In medical applications, BCI revolutionized the development of guided speech generators, orthoses, exoskeletons, wheelchairs, and rehabilitation systems. However, these existing BCI systems are targeted for assisting the periphery (e.g., hands and legs) and not directly treating the brain itself. Our objective is to create a powerful non-invasive BCI-guided neurostimulation platform that directly interacts with motor and cognitive brain networks for personalized rehabilitation of neurological patients. Our proof-of-concept demonstration, based on advanced methods for online analysis of electroencephalographic (EEG) data, provides a novel starting point for the development of neurodiagnostic and neurorehabilitation research and clinical protocols.

During the summer period, the student will learn to use tools to localize the motor imagery in real-time and feed the information into the new robotic system through the neuronavigation software responsible to depict the TMS coil over the cortex in real time.

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.Victor Hugo Souza
Academic contact person: Dr. Victor Hugo Souza, [email protected]

Title of topic 18: Software interface and robotics to control brain stimulation devices

Short task description:
Position available for a summer project to develop open-source software and methods for neuronavigation and robotic arm automation using anatomical brain images. We are looking for a student with great desire to learn new computational and experimental techniques. The project aim is to develop an interface in a neuronavigation software to control a new generation of brain stimulation device that we are creating using a collaborative robotic arm. The student will work mainly with magnetic resonance images and computational visualization tools. There is also a possibility of working with simple electronic components to expand further the applicability of the interface. No specific prior knowledge is needed in brain stimulation or neuronavigation. This job allows the student to improve the programming and automation skills and learn a variety of basic concepts related to electromagnetism, linear algebra, and the brain. The summer job is part of the ConnectToBrain project and more information can be found in the following link: https://www.connecttobrain.eu/

Supervisor of the project: Dr.Victor Hugo Souza
Academic contact person: Dr. Victor Hugo Souza, [email protected]

Title of topic 19: Design, computational modelling, and manufacturing of brain stimulation devices

Short task description:
We offer a summer trainee position for a motivated student to design and manufacture multi-channel brain stimulation transducers for transcranial magnetic stimulation applications. Requirements: You have a great desire to learn new computational and experimental techniques. You have knowledge about electromagnetism, linear algebra, and optimization solvers. Preferably, you have also experience in finite element modelling and CAD software. You are interested in learning about brain stimulation and neuroscience. No prior knowledge of brain stimulation or neuroscience are expected for this position. Tasks: Your tasks include designing brain stimulation transducers based on optimized coil designs, modelling their behavior in high static magnetic field, and analyzing the results. Furthermore, you have the opportunity to fabricate physical models of the transducers using additive manufacturing techniques. Selection criteria: Success in previous studies; motivation and ambition level. Possible additional qualifications and experience obtained in non-standard or informal ways. The summer job is part of the ConnectToBrain project and more information can be found in the following link: https://www.connecttobrain.eu/