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Professor in charge of topic: Riitta Salmelin
Supervisors of the project : Joonas Karhula, Riitta Salmelin
Academic contact persons for further information: Riitta Salmelin, riitta.salmelin@aalto.fi

Title of topic 1: Individual neural markers of cognitive processing

Short task description:
The Imaging Language group (/department-of-neuroscience-and-biomedical-engineering/imaging-language) offers 1-2 summer internship positions. Our multidisciplinary group seeks 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. This year, we offer at least one summer project that is focused on machine learning-based detection of individually unique brain patterns and utilizing these patterns to identify individuals or their characteristics. The student will join in an active research project, with an opportunity to learn and contribute to computational modelling and interpretation of neuroimaging data. 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, R) are considered an asset.

Academic in charge of topic: Marijn van Vliet
Supervisor of the project: Shristi Baral
Academic contact persons for further information: Shristi Baral shristi.baral@aalto.fi and Marijn van Vliet marijn.vanvliet@aalto.fi

Title of topic 2: Investigating semantic integration in the brain using magnetoencephalography (MEG)

Short task description:
Our lab is studying how language is mapped to the visual world. For example, how do we understand that the spoken word "cup" refers to the object we use to drink coffee? To explore this, we are conducting an experiment aimed at uncovering the neural mechanisms that link the language we use to the visual environment we perceive. This research combines MEG with structural MRI to analyze brain activity and structure.

We are looking for research assistant to join our team. Under our guidance, you will recruit participant, perform experiment, and record MEG and (structural) MRI on human volunteers and analyze the data. Given the nature of the study, we are looking for a student who is fluent in Finnish. For this, programming skills and experience with MEG recordings is considered beneficial but not required. Depending on your interests, you'll have a chance to learn more about analysing/visualising MEG data.

Supervisor of the project: Linda Henriksson
Academic contact person for further information: Linda Henriksson, linda.henriksson@aalto.fi

Title of topic 3: Virtual reality for visual neuroscience

Short task description:
Our understanding of the human visual system is mostly from experiments using passive viewing of static 2D stimulus images—to understand real-world visual behavior, we aim to move towards interactive 3D environments during brain imaging experiments. Now we are looking for a motivated student to develop and/or run experiments implemented for virtual reality, and possibly to analyze the collected behavioral, eye gaze and brain responses. The task requires some skills in Python and/or Matlab, skills or interest to learn Unity, and interest in human neuroscience. The exact tasks will be defined such that you could write a BSc thesis or a special assignment based on your work; please describe your interests in the application.

Professor in charge of topic: Hanna Renvall
Supervisor of the project: Maria Nazarova, maria.1.nazarova@aalto.fi
Academic contact person for further information: Maria Nazarova, maria.1.nazarova@aalto.fi

Title of topic 4: TMS motor mapping for  probing and modulating muscle-specific excitation-inhibition interactions at the motor cortex

Short task description:
Are you interested in how brain regulates hand movements and how non-invasive brain stimulation may help motor recovery after stroke? In this project we are focusing on transcranial magnetic stimulation (TMS) cortical motor mapping and assessment of cortico-spinal connectivity for different upper limb muscles to determine how the intricate patterns of the local excitation/inhibition balance at the motor cortex and peculiarities of corticospinal tract functional integrity are involved in the upper limb dexterity in healthy people and stroke patients. The long-term vision of the project is to move from a unidirectional TMS modulation (either excitation or inhibition) towards a more selective modulation of the local inter-muscle E/I balance. We are aiming to perform such neuromodulation by combining TMS with simultaneous functional tuning such as motor execution, motor imagery, peripheral stimulation and TMS-based biofeedback based on the obtained evoked responses. We plan to use both convention MRI-navigated TMS and novel multi-locus TMS developed in the NBE.

Tasks: 
Some example tasks for the intern include (depending on the interests of the candidate): 

• Performing experiments using TMS-EMG, TMS-EEG and 3D motion tracking
• Analysis of TMS-EMG, TMS-EEG, EEG-EMG coherence data
• Analysis of 3D motion tracking data during self-paced movements and TMS-triggered movements

Requirements: 

1. Experience in conducting TMS and EMG/EEG/motion tracking experiments in humans
2. High interest in motor physiology 
3. Programming in Python and Matlab (recommended)

References: 

1. Beck, S., & Hallett, M. (2011). Surround inhibition in the motor system. Experimental Brain Research, 210(2), 165–172. 
2. Cheung, V. C. K., Piron, L., Agostini, M., Silvoni, S., Turolla, A., & Bizzi, E. (2009). Stability of muscle synergies for voluntary actions after cortical stroke in humans. Proceedings of the National Academy of Sciences of the United States of America, 106(46), 19563–19568. 
3. Koponen, L. M., Nieminen, J. O., Mutanen, T. P., Stenroos, M., & Ilmoniemi, R. J. (2017). Coil optimisation for transcranial magnetic stimulation in realistic head geometry. Brain Stimulation. 
4. Nazarova, M., Kozlova, K., Novikov, P., Dobrynina, L., Ivanina, E., & Nikulin, V. V. (2021). Mapping of multiple muscles with transcranial magnetic stimulation : absolute and relative test – retest reliability. February, 1–21. 
5. Nazarova, M., Kulikova, S., Piradov, M. A., Limonova, A. S., Dobrynina, L. A., Konovalov, R. N., Novikov, P. A., Sehm, B., Villringer, A., Saltykova, A., & Nikulin, V. V. (2021). Multimodal Assessment of the Motor System in Patients With Chronic Ischemic Stroke. Stroke, 52(1), 241–249. 
6. Novikov, P. A., Nazarova, M. A., & Nikulin, V. V. (2018). TMSmap – Software for Quantitative Analysis of TMS Mapping Results. Frontiers in Human Neuroscience, 12, 239. https://doi.org/10.3389/fnhum.2018.00239

Professor in charge of topic: Jarno Mäkelä
Supervisor of the project: Jarno Mäkelä
Academic contact person for further information: Jarno Mäkelä, jarno.p.makela@aalto.fi

Title of topic 5: Analysis of Single Molecule Dynamics in Cells

Short task description:
Cellular systems are complex environments where countless proteins, enzymes and other molecules work together to maintain homeostasis. To study these processes, we use state-of-the-art super-resolution microscopy and single molecule tracking to record the movement of individual molecules inside individual live cells. Single molecule dynamics reports on the molecular interactions in real-time, acting as a probe for changes in the cellular environment. The obtained knowledge will help us to understand microorganisms’ adaptation to different environments and the limits of life.

In this summer project, you will analyse microscopy data collected under various environmental perturbations to quantify their effect on protein dynamics. The project involves integrating machine learning methods with modelling approaches to test hypotheses based on experimental observations. The data processing pipeline includes image segmentation and object detection, among others. The ideal candidate should know the basics in Python for scientific computing (e.g. numpy, pandas, matplotlib) and have understanding of machine learning concepts. Prior experience with microscopy techniques is an advantage.

As a part of the research group, you will be trained in methods in state-of-the-art super-resolution microscopy and analysis of single molecule data. There is an option to continue with a MSc thesis. For more info on the group: /en/department-of-neuroscience-and-biomedical-engineering/single-molecule-dynamics-in-cells

Academic contact person for further information: Jani Oksanen, jani.oksanen@aalto.fi & Ivan Radevici, ivan.radevici@aalto.fi 
Possible supervisors: Ivan Radevici, Benoît Behaghel, Pyry Kivisaari (2 open positions)

Title of topic 6: 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 optoelectronics. The possible research tasks deal with a variety of topics related to the device fabrication and characterizing or modeling the devices. Specific topics include e.g. the fabrication and characterization of thin-film devices, setting up automated measurement setups and charaterizing and modeling related devices. 

We are most interested in candidates with studies in physics, compound semiconductor technologies, optoelectronics and/or information technology for measurement automation and analysis. Also fast progress, good marks and interest in learning more about semiconductors is beneficial. 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 primarily 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 (anton.kuzyk@aalto.fi)

Title of topic 7: Fabrication of metal nanostructures with tailored optical responses

Short task description:
Metal nanostructures have great potential for applications in various fields, including photonics, sensing, therapeutics, diagnostics etc. Our research group develops novel methodologies compatible with   large scale fabrication of metal nanostructures with tailored optical responses. In particular, we are interested in the so-called DNA origami based plasmonics and active plasmonic surfaces.

To strengthen our research team, we are looking for highly motivated students with aptitude for interdisciplinary experimental research and interest in DNA nanotechnology, molecular self-assembly, colloidal synthesis, nanofabrication and plasmonics. We expect solid background in applied physics, (bio)nanotechnology and/or nanophotonics. Previous experience in molecular self-assembly and nanomicroscopy (TEM, SEM, AFM) is an advantage. 

As a member of our research group, you will be trained in advanced methods in DNA nanotechnology (especially DNA origami), state-of-the-art electron beam nanomicroscopy techniques (TEM, SEM), and various light-based techniques for characterization of metal nanostructures (spectroscopy and microscopy). Depending on your background and research interests, your work can be related to: 

• Colloidal synthesis on metal nanostructures (preferred background: inorganic chemistry, material science)
• Active plasmonic surfaces (preferred background: material science, physics)
• Optical super-resolution microscopy (preferred background: physics, bioinformation technology)
• Design, fabrication and characterisation of DNA origami nanostructures. 

Your 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:

Examples of our previous works:

Professor in charge of topic: Matias Palva
Supervisor of the project: Matias Palva
Academic contact person for further information: Matias Palva, matias.palva@aalto.fi

Title of topic 8: Brain dynamics and personalized medicine

Short task description:
We are working on understanding the statistical-physics mechanisms governing collective neuronal dynamics. This “collectivity”, also known as “brain criticality” is trait-like across individuals, begets cognitive abilities, and is an endophenotype in many brain diseases. Several lines of brain imaging studies are ongoing 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 development and implementation of data analyses in simulated and real brain imaging data. The project aims to 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 (such as NBE-E4260) 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. 0-1 students will be recruited.

Supervisors of the project: Mia Liljeström
Academic contact person for further information: Mia Liljeström, mia.liljestrom@aalto.fi

Title of topic 9: Development of MEG 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 group, we use both magnetoencephalography (MEG) and peripheral measures, such as electromyography (EMG) and kinematics to study aging and language. 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 EMG 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 suited for a Bachelor’s thesis or a special assignment.

Professor in charge of topic: Iiro Jääskeläinen
Supervisor of the project and academic contact person for further information: Iiro Jääskeläinen, iiro.jaaskelainen@aalto.fi

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 early June to end of August, 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.

Professor in charge of topic: Petri Ala-Laurila
Supervisors of the project: Gabriel Peinado & Petri Ala-Laurila
Academic contact person for further information: Petri Ala-Laurila, petri.ala-laurila@aalto.fi
Title of topic 11: From photons to perception: Linking retinal circuit function to visual behavior

Short task description:
A summer intern position is immediately available in the laboratories of Professor Petri Ala-Laurila & Dr. Gabriel Peinado 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 using a set of unique and beyond-state-of-the-art tools. 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, pupillary measurements in humans and mice and quantitative behavioral measurements.

We are currently seeking to hire  highly motivated summer interns 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 e.g. our papers: Kilpeläinen et al. 2024, Nature Communications; Westö et al. 2022, Current Biology; Koskela et al. 2020, Current Biology; Smeds et al. 2019 Neuron as well as the lab’s webpage:  

Professors in charge of topic: Lauri Parkkonen, Matti Hämäläinen
Supervisors of the project: Lauri Parkkonen, Matti Hämäläinen, Mikael Grön, Joonas Iivanainen, Paavo Hietala, Markus Henttonen, Santeri Ruuskanen
Academic contact person for further information: Lauri Parkkonen (lauri.parkkonen@aalto.fi)

Title of topic 12: 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. Supported by National Institutes of Health (USA), we are continuing the development of the MNE-Python software package, which during the present grant cycle will be in extended to fully integrate high-resolution OPM-MEG data in the analysis and to target signal sources in the whole brain. 

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, simulations and 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; Python programming skills and signal processing are essential in all of them while also good command of university-level mathematics and physics are required in the more system-related tasks. Basic neuroscience would be useful but not mandatory in the brain-measurement and analysis tasks.