Overview
Country: Japan
City: Tokyo
Category: AI Research
Required Background: Applied Math / Computer Science
Tokyo Office: Hybrid Work
Outside Tokyo: Remote Work
Relocation: Possible
Employment Type: Full-Time
Keywords:
Knowledge Graph, NLP, Ontology, Statistical Learning, Intractability, Code Comprehension, Automated Reasoning, Category Theory, Formal Systems
Research Scientist
The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.
Research Scientist
The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.
Overview
Country: Japan
City: Tokyo
Category: AI Research
Required Background: Applied Math / Computer Science
Tokyo Office: Hybrid Work
Outside Tokyo: Remote Work
Relocation: Possible
Employment Type: Full-Time
Keywords:
Knowledge Graph, NLP, Ontology, Statistical Learning, Intractability, Code Comprehension, Automated Reasoning, Category Theory, Formal Systems
Research Scientist
The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.
Overview
Country: Japan
City: Tokyo
Category: AI Research
Required Background: Applied Math / Computer Science
Tokyo Office: Hybrid Work
Outside Tokyo: Remote Work
Relocation: Possible
Employment Type: Full-Time
Keywords:
Knowledge Graph, NLP, Ontology, Statistical Learning, Intractability, Code Comprehension, Automated Reasoning, Category Theory, Formal Systems
What we need help with
1. Ideas. Share and present your own ideas on the agenda. Help others with their ideas by structuring and challenging them.
2. Agenda. Push the research agenda forward. Explore new directions and new points of view on known problems.
3. Investigate. Learn and survey state of the art techniques and theoretical frameworks in AI-related fields.
4. Knowledge Management. Structure the information and keep records of the various ideas.
5. Formalisation. Make scientifically rigorous and grounded statements from vague concepts and thoughts.
Who we are looking for
1. Experience in at least one of these areas: Discrete Knowledge Representation, Statistical Learning Theory, Formal Systems, Formal Logic, Natural Language Processing, Entity Detection and Resolution, Subgraph Matching, Dialogue Systems, Knowledge Extraction, Ontology Building, Automated Reasoning, Category Theory.
2. PhD in Applied Math or Computer Science.
3. English C1 or higher.
What soft skills are essential
1. Commitment. Make and fulfil commitments on time and at a high-quality level.
2. All-Round. Ability to figure out how to do new tasks from adjacent specialisations.
3. Startup Mindset. Focus on the objective, new approaches investigation, fast forwarding orientation.
4. Constructive Discussion. Presenting own arguments, listening to others' arguments, developing the next steps to resolve the difficulty.
A strong advantage would be
1. Agile Experience. We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.
2. The ability to hold thought-leading presentations will help colleagues to understand new concepts and plan their further work.
3. Understanding how to lead the research group.
4. Infrastructure Tools like Notion, Slack, Zotero, Shortcut, Miro.
What we need help with
1. Ideas. Share and present your own ideas on the agenda. Help others with their ideas by structuring and challenging them.
2. Agenda. Push the research agenda forward. Explore new directions and new points of view on known problems.
3. Investigate. Learn and survey state of the art techniques and theoretical frameworks in AI-related fields.
4. Knowledge Management. Structure the information and keep records of the various ideas.
5. Formalisation. Make scientifically rigorous and grounded statements from vague concepts and thoughts.
Who we are looking for
1. Experience in at least one of these areas: Discrete Knowledge Representation, Statistical Learning Theory, Formal Systems, Formal Logic, Natural Language Processing, Entity Detection and Resolution, Subgraph Matching, Dialogue Systems, Knowledge Extraction, Ontology Building, Automated Reasoning, Category Theory.
2. PhD in Applied Math or Computer Science.
3. English C1 or higher.
What soft skills are essential
1. Commitment. Make and fulfil commitments on time and at a high-quality level.
2. All-Round. Ability to figure out how to do new tasks from adjacent specialisations.
3. Startup Mindset. Focus on the objective, new approaches investigation, fast forwarding orientation.
4. Constructive Discussion. Presenting own arguments, listening to others' arguments, developing the next steps to resolve the difficulty.
A strong advantage would be
1. Agile Experience. We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.
2. The ability to hold thought-leading presentations will help colleagues to understand new concepts and plan their further work.
3. Understanding how to lead the research group.
4. Infrastructure Tools like Notion, Slack, Zotero, Shortcut, Miro.
What we need help with
1. Ideas. Share and present your own ideas on the agenda. Help others with their ideas by structuring and challenging them.
2. Agenda. Push the research agenda forward. Explore new directions and new points of view on known problems.
3. Investigate. Learn and survey state of the art techniques and theoretical frameworks in AI-related fields.
4. Knowledge Management. Structure the information and keep records of the various ideas.
5. Formalisation. Make scientifically rigorous and grounded statements from vague concepts and thoughts.
Who we are looking for
1. Experience in at least one of these areas: Discrete Knowledge Representation, Statistical Learning Theory, Formal Systems, Formal Logic, Natural Language Processing, Entity Detection and Resolution, Subgraph Matching, Dialogue Systems, Knowledge Extraction, Ontology Building, Automated Reasoning, Category Theory.
2. PhD in Applied Math or Computer Science.
3. English C1 or higher.
What soft skills are essential
1. Commitment. Make and fulfil commitments on time and at a high-quality level.
2. All-Round. Ability to figure out how to do new tasks from adjacent specialisations.
3. Startup Mindset. Focus on the objective, new approaches investigation, fast forwarding orientation.
4. Constructive Discussion. Presenting own arguments, listening to others' arguments, developing the next steps to resolve the difficulty.
A strong advantage would be
1. Agile Experience. We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.
2. The ability to hold thought-leading presentations will help colleagues to understand new concepts and plan their further work.
3. Understanding how to lead the research group.
4. Infrastructure Tools like Notion, Slack, Zotero, Shortcut, Miro.
How we are different
Not just an ML
People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.
Going beyond
We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.
Safety and Alignment
We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.
How we are different
Not just an ML
People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.
Going beyond
We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.
Safety and Alignment
We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.
How we are different
Not just an ML
People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.
Going beyond
We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.
Safety and Alignment
We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.
What we are offering
Good Salary
That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated.
Hybrid Remote
Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.
Flexible Schedule
Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.
Autonomy
High autonomy is crucial for us – the small and agile team can achieve a breakthrough if its members are professional and independent. However, we promote helping each other. That is crucial too.
Challenging Work
Automated code synthesis is a holy grail: many want it, but nobody has it. You can read more about it on the Company tab or just write to us. We love cross-pollination.
Low Bureaucracy
What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.
What we are offering
Good Salary
That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated.
Hybrid Remote
Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.
Flexible Schedule
Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.
Autonomy
High autonomy is crucial for us – the small and agile team can achieve a breakthrough if its members are professional and independent. However, we promote helping each other. That is crucial too.
Challenging Work
Automated code synthesis is a holy grail: many want it, but nobody has it. You can read more about it on the Company tab or just write to us. We love cross-pollination.
Low Bureaucracy
What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.
What we are offering
Good Salary
That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated.
Hybrid Remote
Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.
Flexible Schedule
Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.
Autonomy
High autonomy is crucial for us – the small and agile team can achieve a breakthrough if its members are professional and independent. However, we promote helping each other. That is crucial too.
Challenging Work
Automated code synthesis is a holy grail: many want it, but nobody has it. You can read more about it on the Company tab or just write to us. We love cross-pollination.
Low Bureaucracy
What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.
Join Our Team
We are looking for specialists for full-time
employment or for part-time collaboration.
Join Our Team
We are looking for specialists for full-time employment or for part-time collaboration.