Quantum information, quantum foundations and gravity

Quantum physics is full of interesting phenomena and applications. For example, according to the principle of quantum superposition, quantum systems can be in superposition of different locations (or of other different physical properties), as beautifully demonstrated in the double slit experiment. Via quantum entanglement, distant quantum particles show joint correlations independently of how far apart they are, challenging the intuitions of Einstein's relativity theory stating that nothing (including information) can travel faster than the speed of light. Using quantum entanglement, quantum teleportation transfers quantum information between distant locations, in an apparent instantaneous way. 

The seeming instantaneous interaction between distant quantum entangled particles led Einstein, together with his colleagues Podolsky and Rosen, to argue that quantum mechanics is an incomplete theory. John Bell provided a mathematical framework to study the intuitions of Einstein, Podolsky and Rosen (EPR), leading to the famous Bell's theorem, which allows to experimentally test the EPR intuitions in the called Bell experiments. The importance of this research area has been recognized by the Nobel prize of Physics in 2022.

Quantum physics is confirmed with overwhelming experimental evidence at the microscopic scales (e.g. at the atomic scale), producing many technological applications. However, there remain unanswered questions for future discovery. Quantum information science gives a modern perspective to analyse many of these questions and provides many important technological applications, for example, quantum cryptography and quantum computation.

The following is an important open problem in quantum physics, called the quantum measurement problem. There are two known types of quantum evolution: the deterministic unitary evolution (e.g. the Schrödinger equation), and the probabilistic collapse of the quantum state upon a quantum measurement. It is unknown when during a quantum measurement the unitary evolution stops, and the collapse takes place: if quantum theory (QT) is universal, then a quantum measurement device should also be described by QT and should therefore be subject to unitary evolution itself. Some proposed solutions are that the quantum state never collapses, as in the many-worlds QT; or that the laws of QT must be changed, as in collapse models.

Another important open problem is to understand how quantum theory and gravity can be unified in a single theory, and in particular whether gravity must necessarily be described by a quantum theory. Einstein’s theory of general relativity (GR), which describes gravity and spacetime, has been confirmed with overwhelming experimental evidence at the macroscopic scales (e.g. at Earth scales and beyond). However, it is in strict conflict with quantum physics. This is because GR assumes that massive systems have well defined locations; while, according to QT, the locations of massive systems can be in undefined locations, as described by quantum superpositions. Thus, to deal with the quantum superpositions of massive systems, GR must be modified. Due to lack of experimental evidence at the interface of GR and QT, very little is known about how to do this. In particular, it is unknown whether a fundamental theory of gravity has any quantum features. Recently, experiments have been proposed to test whether gravity has quantum features, which are believed to be implementable in the near future.

In this research course, we will provide a brief introduction to quantum physics at an elementary level without too much mathematical detail, with an emphasis on quantum information, quantum foundations and connections between quantum physics and spacetime (i.e., gravity). We will discuss various interesting quantum phenomena like quantum superposition, quantum interference, the double slit experiment, quantum entanglement, quantum teleportation, Bell’s theorem and quantum nonlocal causality, the quantum measurement problem, connections between gravity and quantum physics, etc.

The course's objective is to stimulate students' interest in this field of study. By conducting a research project or writing a review paper on quantum physics, students are expected to gain a solid understanding of the subject matter and current debates in the research fields. While no previous knowledge of quantum physics or general relativity is required for this course, a good background in mathematics or physics at high school level is beneficial (but not essential).

Quantum information, quantum computing, quantum cryptography and other quantum technologies

In this research course, we will provide a brief introduction to quantum physics at an elementary level without too much mathematical detail, with an emphasis on quantum information. We will introduce quantum states, qubits, quantum gates, quantum entanglement, quantum teleportation, the quantum no-cloning theorem, quantum computing, quantum cryptography, quantum sensors, and other quantum technologies.

The course's objective is to stimulate students' interest in this field of study. By conducting a research project or writing a review paper on quantum physics, students are expected to gain a solid understanding of the subject matter and current debates in the research fields. No previous knowledge of quantum physics is required for this course. A good background in mathematics or physics at high school level is beneficial (but not essential).

General relativity: fundamentals, applications and open problems

General relativity (GR) is one of our two fundamental theories of physics (together with quantum theory). According to GR, space and time are part of a single entity called spacetime, whose geometry depends on the distribution of energy and mass according to Einstein's equations. The gravitational force arises from the curvature of spacetime. In this course we will discuss at a basic level the theory of GR and some fascinating applications and important open problems. Topics include special relativity (invariance of the speed of light, Lorentz transformations, time dilation, length contraction), curved spacetime, gravitational lensing, black holes, gravitational waves, cosmology (the origin and evolution of the universe), technological applications (e.g, the global positioning system) and some questions related to quantum physics (like gravitational effects on quantum systems, the problem of unification of quantum physics and gravity, and quantum effects on blackholes). This course will be an opportunity for students to develop a deep study on a topic of GR of their choice with guidance by the mentor.

Artificial intelligence in medicine

This course introduces students to the intersection of artificial intelligence and medical imaging, with no prior programming experience required. You will learn Python programming fundamentals and scientific computing while working with actual brain imaging data from the Human Connectome Project (a resource used by leading researchers worldwide!). You will progress from basic coding to building machine learning models that can analyse brain data, gaining hands-on experience in how AI technologies are transforming our understanding of the human brain.

The curriculum blends technical skills with neuroscientific concepts, guiding you through Python programming, data analysis libraries like NumPy and Pandas, and machine learning techniques applied to medical imaging. A key component of the course involves literature exploration, where you will learn to read and understand scientific papers in the field, developing critical research skills. This foundation will prepare you for a personalised project where you can apply your skills to the Human Connectome Project data or explore another dataset or problem aligned with your specific interests.

Ideal candidates for this course are students curious about AI, the brain, or medical technology. If you are interested in how computers can help us understand the human brain, enjoy solving problems with data, or want to learn skills that will be valuable for college and beyond, this course is for you. By the end, you will understand how AI is changing medical research and have learned computer skills that are useful across many science fields, giving you a head start in this exciting area where technology meets human biology.

Investigating the effect of gene mutations on protein function, structure and protein-protein interactions in the context of specific disease using computational tools

Technology evolves and as scientists ask harder questions, currently a lot of studies are focused on genes and proteins, scientists are trying to understand how proteins or genes regulate and control biological processes. Modern methods such as next‐generation sequencing provides understanding of genetic variation associated with diseases or other biological phenomena. The challenge is to distinguish mutations that drive disease or drug resistance from those that are neutral or beneficial to the organism. This requires understanding the effects of missense mutations on gene expression and regulation, as well as on disrupting protein function. Because experimental approaches can be time-consuming and costly there are plenty of computational tools that are used to predict the impacts of mutations on the protein structure and function. In this course it will be taught how to use these tools to solve biological questions.

Introduction to RNA-Seq analysis

This course introduces the fundamentals of bioinformatics and computational biology, focusing on RNA-Seq analysis using publicly available datasets. Students will learn key concepts and techniques related to RNA sequencing, gene expression, and differential analysis through hands-on experience.

By the end of the course, students will have gained practical experience in RNA-seq analysis, developed critical thinking skills for interpreting biological data, and obtained an understanding of how computational tools are applied in genomics research. Here are some potential research topics and questions:

• Genetic variation and gene expression. RNA-seq data can reveal how genetic variants (e.g., SNPs) influence gene expression. Students could study how specific genetic variants affect the expression of nearby genes in a population. Example topic: "Impact of genetic variation on gene expression in a population of healthy individuals".
• Differential gene expression in autoimmune diseases. Using RNA-seq data from patients with autoimmune diseases (e.g., lupus, rheumatoid arthritis), students can identify genes involved in the dysregulation of the immune system. Example topic: "Differential gene expression in rheumatoid arthritis patients".
• Differential gene expression in cancer vs. normal tissue. Students could analyze RNA-seq data from cancer patients (e.g., breast cancer, lung cancer, or leukemia) and compare gene expression profiles between cancerous and normal tissues. This could lead to identifying biomarkers for early cancer detection or potential targets for therapy. Example topic: "Differential gene expression in breast cancer vs. healthy tissue: a search for potential therapeutic targets".

Introduction to consciousness 

We all have an intuitive idea what consciousness is, and yet there is no scientific consensus how it comes about. Ancient scholars such as Aristotle thought that the seat of consciousness is in the heart but today, there is consensus that the brain is crucial to bring about conscious experience. Consciousness neuroscience covers important questions such as: What distinguishes unconscious and conscious sensory events? How do psychedelic drugs change conscious experience? What happens in the brain when someone loses consciousness? How do we dream? Does the rest of the body play a role for consciousness, and if so, how? Can we tell whether someone in a coma might feel pain? 

The first half of the course will introduce students to the fundamentals of consciousness neuroscience: What are the central questions of consciousness science today? How do academics study consciousness in the brain? What are the most important theories of consciousness? What do we know about the bodily self and abnormal bodily experiences (out-of-body experiences, illusions of bodily self-consciousness, phantom limbs, etc.)? We will also cover altered states of consciousness such as psychedelic trips, hypnosis, and disorders of consciousness.

In the second half of the course, students will write their own review papers on a topic in consciousness science they are interested in. We will teach students how to do a literature search and write a review paper.

Introduction to dementia

Given the projected trends in population ageing and population growth, the number of people with dementia is expected triple by 2050 to more than 150 million people. Many of us will be personal affected by dementia by either getting dementia ourselves or caring for someone with dementia.

This first half of the course will provide students with an introduction to dementia and dementia research. This will include a broad overview of brain structure and function, neuropsychology, the various cognitive domains (such as executive functioning, memory, attention), and the different types of brain scans (such as MRI, PET, EEG).

Students will be introduced to the different types of dementias, covering Alzheimer's disease, Vascular dementia, Frontotemporal dementia, Lewy Body dementia, Parkinson's disease, and HIV-associated brain injury. For each type, students will learn about the underlying pathology, brain areas affected and clinical symptoms. They will gain an understanding of how the brain diseases influence cognition, emotion, and behaviour.

The course will also cover dementia prevention. Strong evidence has emerged that 45% of cases of dementia are linked to modifiable factors we can influence ourselves, such as environmental and lifestyle factors. We will look closely at each of these modifiable risk factors for dementia.

In the second half of the course, students will conduct their own review papers on a dementia-related topic they are interested in. Students will be guided on how to conduct a literature search and write a review paper.

🌍 The green revolution — how plants transformed the Earth

This course explores the evolutionary journey of plants from their aquatic origins to their colonization of land, transforming the Earth’s atmosphere and paving the way for animal life. It covers the rise of photosynthesis, the oxygenation of the atmosphere during the great oxidation event, and the subsequent development of complex ecosystems. Special focus is given to how plant innovations, such as vascular tissues and roots, created habitable environments and food sources for terrestrial animals.

Key topics:

1. Origins of photosynthesis: the evolution of cyanobacteria and the first oxygen-producing organisms.
2. The great oxidation event: how plants contributed to atmospheric oxygen and its impact on Earth's climate.
3. Land colonization: the first land plants — mosses, liverworts, and ferns — and their adaptations to terrestrial environments.
4. The carboniferous period: how massive forests sequestered carbon and fueled the development of oxygen-rich atmospheres.
5. Plant-animal co-evolution: the emergence of herbivores, pollinators, and seed dispersers as plant diversity increased.
6. Impact on modern ecosystems: how plant innovations continue to sustain biodiversity and global biogeochemical cycles.

🌿 Masters of adaptation — how plants thrive in dynamic environments

This course delves into the remarkable ability of plants to colonize and adapt to diverse environments, from arid deserts to waterlogged wetlands. It explores the physiological, molecular, and genetic mechanisms that enable plants to sense and respond to fluctuating light, water availability, and temperature. Students will gain insights into how plants acclimate to short-term environmental changes and evolve long-term strategies for survival, shedding light on processes like photomorphogenesis, drought tolerance, and thermal stress response.

Key Topics:

1. Plant sensing and signaling: how plants perceive changes in their environment through photoreceptors, hormone signaling (ABA, auxins), and stress-response pathways.
2. Light acclimation: mechanisms of phototropism, shade avoidance, and dynamic photosynthetic adjustments in response to varying light intensities.
3. Water stress and drought tolerance: stomatal regulation, root architecture adjustments, and osmotic stress responses that allow plants to cope with drought or flooding.
4. Temperature adaptation: heat shock proteins, cold acclimation, and the molecular circuits controlling thermotolerance.
5. Epigenetics and evolutionary adaptations: the role of epigenetic modifications in rapid plant adaptation to environmental stress.
6. Case studies: exploration of extremophile plants like resurrection plants and C4 species, highlighting their unique survival strategies.

🌿 Photosynthesis and plant resilience in a changing world

This advanced course explores the intricate processes of photosynthesis, focusing on its biochemical and physiological mechanisms, regulatory pathways, and protective responses. It delves into how plants finely tune photosynthesis to cope with dynamic environmental conditions—light fluctuations, temperature changes, and seasonal shifts. The course emphasizes how these adaptive strategies not only ensure plant survival but also play a crucial role in ecosystem stability and global carbon cycling. In the context of climate change, the course will address how rising temperatures, drought, and CO₂ levels impact photosynthesis, and the potential for bioengineering plants to enhance their photosynthetic efficiency.

Key topics:

1. The biochemistry of photosynthesis:
o The light-dependent reactions (photophosphorylation, photosystems I and II, electron transport chain).
o The Calvin cycle and carbon fixation strategies (C3, C4, and CAM pathways).
2. Regulation of photosynthesis:
o Feedback mechanisms controlling the balance between light capture and carbon assimilation.
o The role of stomatal conductance and its impact on water use efficiency and CO₂ uptake.
3. Protective mechanisms against stress:
o Non-photochemical quenching (NPQ) and the dissipation of excess light energy.
o Reactive oxygen species (ROS) and antioxidant responses.
o Photorespiration and its controversial role in plant stress responses.
4. Daily and seasonal regulation:
o Circadian rhythms and their control of photosynthetic processes.
o Acclimation to changing photoperiods and seasonal variations in light and temperature.
5. Photosynthesis in a changing climate:
o The effects of elevated CO₂ levels on photosynthetic rates and water use.
o Heat stress and its impact on photosystem stability and enzyme activity.
o The future of plant productivity and crop resilience in the face of global warming.
6. Bioengineering and innovation:
o Genetic modifications to improve photosynthetic efficiency.
o Case studies on engineered crops with enhanced carbon fixation or reduced photorespiration.

🌿Plant biotechnology and innovation — harnessing nature for a sustainable future

This course explores the cutting-edge advancements in plant science and biotechnology, focusing on how innovative technologies like artificial intelligence (AI), gene editing, and bioengineering are transforming agriculture, energy, and medicine. Students will gain a deep understanding of the scientific breakthroughs driving sustainable solutions — from developing climate-resilient crops to producing biofuels and plant-based medicines. The course also highlights how plants' natural processes are harnessed to tackle global challenges such as food security, environmental sustainability, and renewable energy production.

Key Topics:

1. Artificial intelligence in plant science:
o Using AI to model plant growth, predict traits, and optimize breeding strategies.
o Case studies on AI-driven solutions for water-efficient crops and nutrient absorption.
2. Gene editing and CRISPR Technologies:
o Principles of CRISPR/Cas9 and its applications in developing disease-resistant and drought-tolerant plants.
o Ethical considerations and regulatory frameworks in plant genome editing.
3. Plants and renewable energy:
o Biofuel production from plant biomass and algae as an eco-friendly alternative to fossil fuels.
o Innovations in engineering high-biomass crops for enhanced bioenergy output.
4. Sustainable agriculture and vertical farming:
o The role of genetic engineering in boosting crop yields and reducing agricultural inputs (water, fertilizers).
o Vertical farming techniques: advantages, challenges, and real-world examples.
5. Plant-based medicines and human health:
o Discovery of plant-derived compounds for treating diseases (e.g., anticancer agents, antimalarials).
o Biotechnological approaches to enhance the production of medicinal plant metabolites.
6. Future perspectives:
o The intersection of plant science and synthetic biology: designing plants with novel traits.
o Climate change adaptation strategies: leveraging plant biotechnology to build a food-secure future.

Introduction to synthetic biology with emphasis on cloning and protein engineering

This course offers an engaging and comprehensive introduction to synthetic biology, with a special focus on cloning and protein engineering. Designed for high school and undergraduate students, the course combines theoretical learning with practical, computer-based simulations to explore the design, construction, and modification of biological systems. Using state-of-the-art in silico tools, students will gain hands-on experience in genetic manipulation, protein design, and modeling. 

Course Overview: Synthetic biology is an interdisciplinary field that blends biology with engineering principles to design and construct new biological parts, devices, and systems. This course introduces key concepts in synthetic biology, focusing on the practical applications of cloning techniques and protein engineering to innovate in areas such as biotechnology, medicine, and environmental sustainability. All learning will be done through online simulations and software platforms, allowing students to gain computational experience in modern biotechnology techniques.

Key topics covered:

1. Introduction to synthetic biology:
   • Overview of synthetic biology and its evolution.
   • Key principles of designing biological systems and the synthetic biology "design-build-test-learn" cycle.
   • Exploration of ethical, environmental, and societal implications of synthetic biology research and applications.
2. In silico cloning techniques:
   • Introduction to molecular cloning and virtual gene construction tools.
   • Overview of plasmids, restriction enzymes, and ligation protocols in an online setting.
   • Use of virtual PCR to amplify DNA sequences and simulate cloning processes.
   • Simulating transformation and selection strategies in microbial systems.
   • Analysis of cloning efficiency and troubleshooting common challenges using software tools.
3. Gene synthesis and assembly (in silico):
   • Virtual gene design, optimization, and synthesis using computational tools.
   • Introduction to standardized biological parts (e.g., BioBricks) and in silico assembly of genetic circuits.
   • Using software to design complex genetic systems and simulate their function.
   • Tools for evaluating the feasibility and efficiency of synthetic gene assembly.
4. In silico protein engineering:
   • Basics of protein structure and function, with a focus on engineering proteins for desired outcomes.
   • Virtual platforms to design and optimize protein sequences for expression in various host systems.

5. Applications in biotechnology and medicine:
   • Case studies of computational drug design, gene therapy simulations, and vaccine development through synthetic biology.
6. Ethical, regulatory, and safety considerations:
   • Discussions on the ethical implications of synthetic biology innovations.

Learning approach and tools: This course will be taught entirely online, using in silico (computer-based) tools and simulations. Students will have access to a range of software platforms for gene synthesis, protein engineering, and system modeling. Interactive tutorials and virtual labs will enable students to:

• Simulate DNA cloning, protein expression, and system optimization.
• Visualize genetic sequences, predict protein structures, and assess the functionality of synthetic biological systems.
• Collaborate in virtual group projects to solve real-world synthetic biology challenges.

Students will engage in project-based learning, where they will apply the principles of synthetic biology to design and test virtual genetic circuits, optimize proteins for specific tasks, and troubleshoot cloning or protein engineering challenges through simulations.

Introduction to social inequalities

Our world today is still highly unequal. According to Oxfam, eight billionaires have as much wealth as the poorest half of the world, about 3.6 billion people. This type of inequality is not only shaped by the amount of money a person has, but by multiple socially constructed categories such as gender and race. This course is an introduction to the diverse social causes and impacts of global inequalities through an intersectional lens.

You will learn about the different types of inequalities that exist and the way they relate to each other, building a conceptual foundation. This knowledge will serve as a springboard for developing your own literature exploration project, where you can dive deeper into topics that interest you, with the mentor's guidance and support throughout the process.

Key topics

1. Class: the difference between income, wealth, and class.
2. Gender: the concept of gender, its implications, and intersectionality as a feminist analytical tool.
3. Race: historical and contemporary construction of racialised populations and whiteness.
4. Coloniality: colonial legacies and the global division of labour.
5. Environmental inequalities: contemporary examples of how all the categories studied manifest themselves in the context of the climate emergency.

Quantum mechanics describes physical systems at microscopic scales, for example, molecules, atoms, subatomic particles, photons, etc. The quantum phenomena are strange and fascinating with many important technological applications. 

Quantum superposition is a fundamental quantum property, which implies quantum entanglement, quantum teleportation, quantum cryptography, quantum computing, etc.

General relativity (GR) is one of our two fundamental theories of physics (together with quantum theory). According to GR, space and time are part of a single entity called spacetime, whose geometry depends on the distribution of energy and mass according to Einstein's equations. The gravitational force arises from the curvature of spacetime. GR has fascinating predicitons, for example, time dilation and length contraction in different inertial reference frames, the invariance of the speed of light, the curvature of spacetime near massive bodies, gravitational lensing, black holes, gravitational waves, the origin and evolution of the universe, gravitational effects on quantum systems, etc. The global positioning system is a technology exploiting GR that we use in our everyday life (for example, in online maps and navigation tools like Google maps).

Traits and characteristics in living organism and many viruses including the growth, development, functioning, and reproduction are passed from generation to generation thanks to genes. Genes are segments of organic molecules called deoxyribonucleic acid (DNA), which are made up of two strands in the form of a double helix. DNA stores information that is essential for producing proteins and maintaining the functions of cells, and it is passed down from one generation to the next, determining inherited traits.

Microbiology studies microorganisms, which are organisms that are too small to see without a microscope, for example bacteria, viruses, and cells. At the core of much biological research is the study of proteins—molecules that are fundamental to every process in life. For example, bacteria, often seen as harmful, can be harnessed for their ability to produce proteins, which has broad applications in medicine and biotechnology. This process, known as protein expression, is key for developing life-saving drugs, vaccines, and enzymes used in everything from food production to industrial applications.

Plant science is a fascinating and rapidly evolving field that seeks to understand the living world of plants in all their complexity. It explores the structure, function, growth, and evolution of plants, as well as their interactions with the environment. The goal is to unlock the secrets of plant life and use this knowledge to tackle global challenges, from food security to climate change.

Neuroscience is the study of the brain and the nervous system. The brain is the organ of the mind, and the experience of 'being you'. Your brain and mind are shaped by the environment in which you live and by your experiences. The brain is the most specialized organ, receiving information from the senses (vison, hearing, touch, taste, smell, balance, visceral sensation, etc.), processing the information (cognition, thoughts, intelligence, etc.) and coordinating motor control (via muscle activity and chemical activity, i.e., via hormones). Neurons are cells that comprise the primary components of the nervous systems.  They transmit information throughout the body via electrical and chemical signals. The human brain has approximately 100 billion neurons, making approximately 100 trillion synaptic connections. For comparison, the estimated number of galaxies in the observable universe is 2 trillion. Neuroscience is a fascinating field with many important research problems.

Synthetic biology is an interdisciplinary field combining principles of biology, engineering and computer science to develop new biological parts, devices and systems or to redesign existing biological systems. It comprises the categories of bioengineering, synthetic genomics, protocell synthetic biology, unconventional molecular biology, and in silico techniques.

Artificial intelligence (AI) is a research field that develops methods, algorithms and software to enable computers to learn and perform highly advanced functions. AI plays a very important role in many technologies nowdays with boad applications, for example, in web search engines (e.g., Google), virtual assistants (e.g., Siri and Alexa), autonomous vehicles, generation of human-like text (e.g., ChatGPT and DeepSeek), strategy games (e.g., chess and Go). AI is also becoming a very important tool in science research with importnat applications, for example in medicine.

Robotics is a research field focusing on the design, construction and operation of robots. Robots have many technological applications, for example, in manufacturing (e.g., in the automotive industry), construction, agriculture, medicine (e.g., in robot-assisted surgery), space exploration (including Mars rovers), autonomous transport (e.g., self-driving cars), entertainment (e.g., drone light shows, robot combat and robot racing), domestic robots, etc.

Social sciences and humanities are related fields of study focusing on the relationships among members within a society and the fundamental aspects of human society and culture. Disciplines included in social science are sociology, economics, anthropology, archaeology, geography, linguistics, psychology, culturology, political science, etc. Disciplines included in humanities are philosophy, history, religion, literature, arts, etc.