The research group focuses on problems of practical use of algorithms, ranging from economic applications, through learning data structures, to parallel algorithms for data science. Our teams focus not only on scientific development but also on the possibility of the practical application of the created solutions in business and the economy. We create innovations that will soon be implemented, allowing you to see the real effects of your work. If you have similar ambitions, are looking for scientific challenges and want to prove yourself in actual market conditions, we invite you to apply.

General must-have requirements

If you are a student or graduate of Mathematics, Computer Science, Information Technology or a related discipline and would like to pursue a career in research, then share your plans with us by applying for this position.

PhD Candidate

You will carry out research and development work related to issues such as: the use of IT tools in the digital economy, learning data structures, algorithms for data science, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities, teaching a minimum of 60 hours per year.

Must-have requiremets

A degree (Master’s or equivalent) in computer science, information technology or a related discipline from a leading university, excellent programming skills, curiosity and great interest in machine learning, artificial intelligence or IT tools for the digital economy, fluency in English.

Nice-to-have requiremets

We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.

PostDoc

You will carry out research and development work related to issues such as: the use of IT tools in the digital economy, learning data structures, algorithms for data science, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.

Must-have requiremets

Educational background: PhD in Science, preferred majors: Computer Science, or Mathematics or other science majors with experience in working with AI, experience in machine learning, English language skills at an advanced level, very good programming skills, a proactive approach to solving scientific problems and issues, strong analytical and critical thinking skills, ability to work in a team.

Nice-to-have requiremets

We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.

Contact: Piotr Sankowski, PhD, ScD (phd [ at ] ideas-ncbr.pl)

The team develops neural networks that generate graphs. These solutions are oriented towards the automatic design of structures naturally represented by graphs, such as molecules or energy networks. Known methods for generating graphs are based on an assumed limitation on the size of the graph and are thus not scalable. How to generate arbitrarily large graphs that meet set functional requirements? We are developing methods that address this challenge. https://ideas-ncbr.pl/en/badania/learning-in-control-graphs-and-networks/

PhD Candidate

You will carry out research and development work related to issues such as: deep reinforcement learning; automated trading; graph neural networks; energy grid control; continual learning; other related scientific issues. Your work will be research-focused with minimal teaching responsibilities, teaching a minimum of 60 hours per year.

Must-have requiremets

Programming in Python; knowledge of libraries (at least one): PyTorch, TensorFlow; experience in machine learning; proactive approach to solving scientific problems and issues; strong analytical and critical thinking skills; strong background in mathematics; ability to work in a team; fluency in English.

Nice-to-have requiremets

We would be pleased to see in your application: scientific publications, especially at good ML conferences and/or other signs of outstanding academic performance.

PostDoc

You will carry out research and development work related to issues such as: deep reinforcement learning, automated trading, graph neural networks, energy grid control, continual learning; other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.

Must-have requiremets

Programming in Phyton, fluent knowledge of libraries (at least) one: PyTorch, TensorFlow, research experience in machine learning including publications at ML conferences/journals, proactive approach to solving scientific problems and issues, strong analytical and critical thinking skills, strong background in mathematics, ability to work in a team, fluency in English.

Nice-to-have requiremets

We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.

Contact: Paweł Wawrzyński, PhD, DSc (phd [ at ] ideas-ncbr.pl)

With expertise in diverse areas such as geometric modeling, geometry processing, computational fabrication, and machine learning, we strive to create algorithmic solutions for digital content generation. Our research efforts are dedicated to revolutionizing content creation, geometry generation, realistic rendering, and physical simulations in applications ranging from computer games and movie productions to virtual reality and 3D design. As a part of our group, you will have the opportunity to work on cutting-edge research projects, publish in top-tier conferences and journals, and collaborate with a diverse team of experts. This PhD project is an exciting opportunity to delve into the promising and rapidly evolving field of differentiable neural rendering. This is a novel area at the crossroads of machine learning and computer graphics, where traditional rendering techniques meet advanced neural networks. The primary objective of this research is to develop innovative methods for differentiable neural rendering with applications in CGI for visual effects for film, TV, and advertisement productions. The project involves developing a framework where changes in the output image can be traced back to changes in input parameters, such as object shapes, light positions, or material properties. Leveraging this, the project aims to optimize these parameters to improve the quality of the rendered image.

PhD Candidate

Must-have requiremets

A strong background in computer science, mathematics, or related disciplines; MSc graduate or last year student; experience in machine learning; knowledge of libraries such as TensorFlow or PyTorch; familiarity with differentiable or neural rendering would be an advantage but is not a requirement; proficient programming skills, preferably in Python; proactive approach to solving scientific problems and issues; strong analytical and critical thinking skills; ability to work in a team; fluency in English.

Nice-to-have requiremets

We would be pleased to see in your application: references with min. 1 contact to people, who can recommend you.

Contact: Przemysław Musialski, PhD, Assoc. Prof. (phd [ at ] ideas-ncbr.pl)

The team research so far has concentrated mainly on classical graph processing problems such as reachability and shortest paths computation, especially in dynamic, fault-tolerant, and parallel settings that address some of the most significant challenges of today’s large networks. Lately, we have also been exploring connections between classical algorithm design and machine learning.

PhD Candidate

You will cooperate with scientists carrying out research and development work related to issues such as: planning and theoretical analysis of graph algorithms – in particular within the upcoming project NCN (summary) implementation and experimental evaluation of graph algorithms on the modern parallel machines, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.

Must-have requiremets

• a degree (Master’s or equivalent) in computer science, information technology or a related discipline from a leading university
• solid understanding of the mathematics and IT basics in terms of: algorithms and data structures, computational complexity, discrete mathematics, probability theory and linear algebra,
• programming skills
• fluency in English

Nice-to-have requiremets

• experience in science work or programming contests in regard to algorithms would be nice to have.

Intern

You will cooperate with scientists carrying out research and development work related to issues such as:

• planning and theoretical analysis of graph algorithms – in particular within the upcoming project NCN
• implementation and experimental evaluation of graph algorithms on the modern parallel machines
• other related scientific issue
• a minimum commitment of 20 hours per week.

Must-have requiremets

• solid understanding of the mathematics and IT basics in terms of: algorithms and data structures, computational complexity, discrete mathematics, probability theory and linear algebra
• programming skills
• fluency in English

Nice-to-have requiremets

• experience in science work or programming contests in regard to algorithms would be nice to have.

Contact: Adam Karczmarz, PhD (phd [ at ] ideas-ncbr.pl)

The Independent Research Team aims to challenge the current approach that avoids contacts and intend robots to leverage contacts for perception and action. Focuses on using vision and tactile sensing to provide robots with detailed understanding of the environment’s physics. We focus on the scientific development of our employees and the practical application of research results.

General must-have requirements

If you are a student or graduate of Mathematics, Computer Science, Information and Communication Technology or a related discipline and would like to pursue a career in research, then share your plans with us by applying for this position.

PhD Candidate

You will carry out research and development work related to issues such as: machine learning methods to enable robots to interact with the environment taking into account physical phenomena of this process, interactive perception, representation learning and reinforcement learning, agile robotic manipulation of deformable objects, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.

Must-have requiremets

Educational background: MSc graduate or last year student, preferred majors: Robotics, Control, Computer Science or other science majors related to robotics and machine learning, experience in robotics and machine learning, practical experience in software development for robotic learning, including programming skills with the use of such libraries as: Robot Operating System 2, Gazebo, MuJoCo,kr PyTorch, TensorFlow, Keras, OpenCV, Open3D, PCL, advanced level of English, very good programming skills, proactive approach to solve problems and scientific issues, excellent analytical and critical thinking skills, ability to work in a team.

Nice-to-have requiremets

We would be pleased to see in your application: experience in implementing robotic solutions experience in efficient methods of machine learning, senor data processing, robot control references with min. 1 contact to person, who can recommend you.

PostDoc

You will carry out research and development work related to issues such as: machine learning methods to enable robots to interact with the environment taking into account physical phenomena of this process, interactive perception, representation learning and reinforcement learning, agile robotic manipulation of deformable objects, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.

Must-have requiremets

Educational background: PhD in Science, preferred majors: Robotics, Control, Computer Science or other science majors related to robotics and machine learning, experience in robotics and machine learning, practical experience in software development for robotic learning, including programming skills with the use of such libraries as: Robot Operating System 2, Gazebo, MuJoCo,kr PyTorch, TensorFlow, Keras, OpenCV, Open3D, PCL scientific publications presented during the most important thematic conferences such as: ICRA, IROS, RSS, CORL or top tier robotics journals such as: Science Robotics, Transactions on Robotics, Robotics and Automation Letters, The International Journal of Robotic Research, Robotics and Autonomous Systems advanced level of English, very good programming skills, proactive approach to solve problems and scientific issues, excellent analytical and critical thinking skills, ability to work in a team.

Nice-to-have requiremets

We would be pleased to see in your application: experience in implementing robotic solutions experience in efficient methods of machine learning, senor data processing, robot control references with min. 1 contact to person, who can recommend you.

Contact: Krzysztof Walas, PhD (phd [ at ] ideas-ncbr.pl)

This research looks at how to make computer vision machine learning models more efficient. Inspired by green and sustainable practices, we’re not just trying to limit how we train these models. Instead, we’re looking at how to use our existing resources and information better. Our goal is to start a new approach called zero-waste machine learning that aims to save on computational efforts and use fewer resources. It relies on three pillars: sustainable machine learning for autonomous machines, knowledge accumulation in continually trained models and conditional computations.

General must-have requirements

If you are a student or graduate of Mathematics, Computer Science, Information Technology or a related discipline and would like to pursue a career in research, then share your plans with us by applying for this position.

Team leader - Conditional Computations

As a team leader you will be responsible to oversee the development of a team consisting of PhD students and post-docs that will work in the area of conditional computations (a.k.a. dynamic computations).

Must-have requiremets

Educational background: PhD in Science, preferred majors: Computer Science, or Mathematics or other science majors with experience in working with AI, experience in machine learning, English language skills at an advanced level, very good programming skills, a proactive approach to solving scientific problems and issues, strong analytical and critical thinking skills, ability to work in a team.

Nice-to-have requiremets

Scientific track record of publications presented during the most important thematic conferences such as: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, ACL, EMNLP, KDD, AAAI, IJCAI, COLT, UAI, AISTATS or in scientific journals TPAMI, IJCV, etc. Experience as a team leader is a plus.

PostDoc

As a post-doc, you will carry out research related to the following topics: efficient methods of machine learning in applications related to computer vision, algorithms of creating efficient representation of data, including multimodal data, as well as methods of machine learning concentrated on long-term development of artificial intelligence (continual learning, methods with reduced supervision including self-supervision methods, non-supervised methods and generative models).

Must-have requiremets

Scientific track record of publications presented during the most important thematic conferences such as: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, ACL, EMNLP, KDD, AAAI, IJCAI, COLT, UAI, AISTATS or in scientific journals TPAMI, IJCV, etc.

Nice-to-have requiremets

Scientific track record of publications presented during the most important thematic conferences such as: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, ACL, EMNLP, KDD, AAAI, IJCAI, COLT, UAI, AISTATS or in scientific journals TPAMI, IJCV, etc.,

PhD Student

As a PhD student, you will carry out state-of-the-art research on topics related to: performance-based machine learning, deep neural networks, continual learning, conditional computations, sustainable machine learning.

Must-have requiremets

A degree (Master’s or equivalent) in computer science, information technology or a related discipline from a leading university, excellent programming skills, curiosity and great interest in machine learning and/or artificial intelligence, fluency in English.

Nice-to-have requiremets

Scientific track record of publications presented during the most important thematic conferences such as: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, ACL, EMNLP, KDD, AAAI, IJCAI, COLT, UAI, AISTATS or in scientific journals TPAMI, IJCV, etc.,

Contact: Tomasz Trzciński (tomasz.trzcinski [ at ] ideas-ncbr.pl)